xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

4e4ad652bab35390c7573ef492731fc6c77f64d0

66

py

Python

content/home/f.py

jasonlin316/academic-kickstart

38760e636d77c835526a313756d8ed917467acab

[ "MIT" ]

null

content/home/f.py

jasonlin316/academic-kickstart

38760e636d77c835526a313756d8ed917467acab

[ "MIT" ]

null

content/home/f.py

jasonlin316/academic-kickstart

38760e636d77c835526a313756d8ed917467acab

[ "MIT" ]

null

# -*- coding: UTF-8 -*- a1 = 3.14159 print("number is %05.1f" %a1)

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py

Python

sympyosis/__main__.py

ZechCodes/sympyosis

0c7315a08fc91d2d074b42f0aeb5d04c6f3f22d1

[ "MIT" ]

null

sympyosis/__main__.py

ZechCodes/sympyosis

0c7315a08fc91d2d074b42f0aeb5d04c6f3f22d1

[ "MIT" ]

null

sympyosis/__main__.py

ZechCodes/sympyosis

0c7315a08fc91d2d074b42f0aeb5d04c6f3f22d1

[ "MIT" ]

null

from sympyosis.app import App App.launch()

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0915865c87184279d8c0b14699c705a7ee4695dd

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py

Python

mission_control/test/test_utilities/__init__.py

ChrisScianna/ROS-Underwater-RnD

f928bcc6b19a830b98e2cc2aedd65ff35b887901

[ "BSD-3-Clause" ]

null

mission_control/test/test_utilities/__init__.py

ChrisScianna/ROS-Underwater-RnD

f928bcc6b19a830b98e2cc2aedd65ff35b887901

[ "BSD-3-Clause" ]

85

2020-10-05T11:44:46.000Z

2021-09-08T14:31:07.000Z

mission_control/test/test_utilities/__init__.py

ChrisScianna/ROS-Underwater-RnD

f928bcc6b19a830b98e2cc2aedd65ff35b887901

[ "BSD-3-Clause" ]

1

2021-11-04T13:18:17.000Z

from .mission_control_interface import MissionControlInterface from .waits import wait_for

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py

Python

angr_platforms/tricore/rcrw_instr.py

shahinsba/angr-platforms

86f9ea90c396fb5561d0196a2d1a873e573b0294

[ "BSD-2-Clause" ]

null

angr_platforms/tricore/rcrw_instr.py

shahinsba/angr-platforms

86f9ea90c396fb5561d0196a2d1a873e573b0294

[ "BSD-2-Clause" ]

null

angr_platforms/tricore/rcrw_instr.py

shahinsba/angr-platforms

86f9ea90c396fb5561d0196a2d1a873e573b0294

[ "BSD-2-Clause" ]

null

#!/usr/bin/env python3 """ rcrw_instr.py Implementation of RCRW format instructions. """ from pyvex.lifting.util import Type, Instruction from .rtl import extend_to_32_bits from .logger import log_this class RCRW_INSERT(Instruction): """ Insert Bit Field instruction: op = 0xD7 op2 = 0x00 (3-bit) User Status Flags: no change. """ name = 'RCRW_INSERT' op = "{0}{1}".format(bin(0xd)[2:].zfill(4), bin(7)[2:].zfill(4)) op2 = "{0}".format(bin(0)[2:].zfill(3)) bin_format = op + 'b'*4 + 'a'*4 + op2 + 'w'*5 + 'c'*4 + 'd'*4 def parse(self, bitstrm): data = Instruction.parse(self, bitstrm) width = int(data['w'], 2) data = {"a": int(data['a'], 2), "const4": int(data['b'], 2), "c": int(data['c'], 2), "w": width, "d": int(data['d'], 2)} log_this(self.name, data, hex(self.addr)) return data def get_dst_reg(self): return "d{0}".format(self.data['c']) def get_const4(self): return self.constant(self.data['const4'], Type.int_32) def get_d_d(self): return self.get("d{0}".format(self.data['d']), Type.int_32) def get_d_a(self): return self.get("d{0}".format(self.data['a']), Type.int_32) def fetch_operands(self): return self.get_d_a(), self.get_d_d(), self.get_const4() def compute_result(self, *args): d_a = args[0] d_d = args[1] const4 = args[2] pos = (d_d & 0x1f).cast_to(Type.int_8) width = self.data['w'] const_1 = self.constant(1, Type.int_32) mask = ((const_1 << width)-1) << pos result = (d_a & ~mask) | ((const4 << pos) & mask) # undefined result if (pos + width) > 32 cond_undefined = extend_to_32_bits(((pos + width) >> 5) == 0) result = result & cond_undefined.cast_to(Type.int_32) return result def commit_result(self, res): self.put(res, self.get_dst_reg()) class RCRW_IMASK(Instruction): """ Insert Mask instruction: op = 0xD7 op2 = 0x01 (3-bit) User Status Flags: no change. """ name = 'RCRW_IMASK' op = "{0}{1}".format(bin(0xd)[2:].zfill(4), bin(7)[2:].zfill(4)) op2 = "{0}".format(bin(1)[2:].zfill(3)) bin_format = op + 'b'*4 + 'a'*4 + op2 + 'w'*5 + 'c'*4 + 'd'*4 def parse(self, bitstrm): data = Instruction.parse(self, bitstrm) width = int(data['w'], 2) data = {"const4": int(data['b'], 2), "c": int(data['c'], 2), "w": width, "d": int(data['d'], 2)} log_this(self.name, data, hex(self.addr)) return data def get_dst_reg(self): return "d{0}".format(self.data['c']) def get_const4(self): return self.constant(self.data['const4'], Type.int_32) def get_d_d(self): return self.get("d{0}".format(self.data['d']), Type.int_32) def fetch_operands(self): return self.get_d_d(), self.get_const4() def compute_result(self, *args): d_d = args[0] const4 = args[1] pos = (d_d & 0x1f).cast_to(Type.int_8) width = self.data['w'] const_1 = self.constant(1, Type.int_32) result_1 = ((const_1 << width)-1) << pos result_2 = const4 << pos # undefined result if (pos + width) > 32 cond_undefined = extend_to_32_bits(((pos + width) >> 5) == 0) result_1 = result_1 & cond_undefined.cast_to(Type.int_32) result_2 = result_2 & cond_undefined.cast_to(Type.int_32) self.put(result_1, "d{0}".format(self.data['c']+1)) self.put(result_2, "d{0}".format(self.data['c']))

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0929ee1a3ba43c4d262be960ab540b8377ec91f2

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py

Python

__main__.py

jack1142/zxpy

fb527cc69169dc884e48bf194c77972a54d1123f

[ "MIT" ]

null

__main__.py

jack1142/zxpy

fb527cc69169dc884e48bf194c77972a54d1123f

[ "MIT" ]

null

__main__.py

jack1142/zxpy

fb527cc69169dc884e48bf194c77972a54d1123f

[ "MIT" ]

null

import zx zx.cli()

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py

Python

preprocessing/__init__.py

zhigangjiang/LGT-Net

d9a619158b2dc66a50c100e7fa7e491f1df16fd7

[ "MIT" ]

11

2022-03-03T17:49:33.000Z

2022-03-25T11:23:11.000Z

preprocessing/__init__.py

zhigangjiang/LGT-Net

d9a619158b2dc66a50c100e7fa7e491f1df16fd7

[ "MIT" ]

null

preprocessing/__init__.py

zhigangjiang/LGT-Net

d9a619158b2dc66a50c100e7fa7e491f1df16fd7

[ "MIT" ]

1

2022-03-04T06:39:50.000Z

""" @date: 2021/7/5 @description: """

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5

11c4f2b19da7b5c889286e32379929823ae6af4b

201

py

Python

memento.py

oleksiygarnik/Vehicles-trajectory-detection

f66b7f9584783a49c77c4c30220b149f59350fdc

[ "MIT" ]

null

memento.py

oleksiygarnik/Vehicles-trajectory-detection

f66b7f9584783a49c77c4c30220b149f59350fdc

[ "MIT" ]

null

memento.py

oleksiygarnik/Vehicles-trajectory-detection

f66b7f9584783a49c77c4c30220b149f59350fdc

[ "MIT" ]

null

from collections import deque class PointContainerMemento(object): def __init__(self): self.points = [] class PlotHistory(object): def __init__(self): self.history = deque()

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5

11db17a1f40574a96fc09f79ce09c9e00334d162

39

py

Python

select2/models/__init__.py

SpectralAngel/django-select2-forms

a1e7b48ade3b0a6bfbb3dbf5ddb880634b56da08

[ "BSD-2-Clause" ]

59

2015-02-19T01:44:58.000Z

2022-03-10T00:25:29.000Z

select2/models/__init__.py

SpectralAngel/django-select2-forms

a1e7b48ade3b0a6bfbb3dbf5ddb880634b56da08

[ "BSD-2-Clause" ]

34

2015-01-08T13:43:33.000Z

2022-02-24T19:15:20.000Z

select2/models/__init__.py

SpectralAngel/django-select2-forms

a1e7b48ade3b0a6bfbb3dbf5ddb880634b56da08

[ "BSD-2-Clause" ]

26

2015-01-07T17:41:44.000Z

2021-02-26T08:56:09.000Z

from .base import SortableThroughModel

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11ed1fbfc9611a4ed5afbbee45476fbb091ec170

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py

Python

bugtests/test262p/y.py

doom38/jython_v2.2.1

0803a0c953c294e6d14f9fc7d08edf6a3e630a15

[ "CNRI-Jython" ]

null

bugtests/test262p/y.py

doom38/jython_v2.2.1

0803a0c953c294e6d14f9fc7d08edf6a3e630a15

[ "CNRI-Jython" ]

null

bugtests/test262p/y.py

doom38/jython_v2.2.1

0803a0c953c294e6d14f9fc7d08edf6a3e630a15

[ "CNRI-Jython" ]

null

assert __name__ == "test262p.y"

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ee9ace7e643ab890a180d0eb88dd59918dc8ec94

285

py

Python

app/utils.py

youssefhoummad/ni9ash

b8d69c72e5b9c1e8dae170bda74d599072e3d5c1

[ "MIT" ]

null

app/utils.py

youssefhoummad/ni9ash

b8d69c72e5b9c1e8dae170bda74d599072e3d5c1

[ "MIT" ]

null

app/utils.py

youssefhoummad/ni9ash

b8d69c72e5b9c1e8dae170bda74d599072e3d5c1

[ "MIT" ]

null

def get_object_or_none(model, *args, **kwargs): try: return model._default_manager.get(*args, **kwargs) except model.DoesNotExist: return None def get_object_or_this(model, this, *args, **kwargs): return get_object_or_none(model, *args, **kwargs) or this

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5

e12bfc4c9b09f653693774e642c19f31f2f2979b

174

py

Python

dataset_creation/__init__.py

jbesty/irep_2022_closing_the_loop

db88bd3ead2231636aa46e36f0a0272b17437612

[ "MIT" ]

null

dataset_creation/__init__.py

jbesty/irep_2022_closing_the_loop

db88bd3ead2231636aa46e36f0a0272b17437612

[ "MIT" ]

null

dataset_creation/__init__.py

jbesty/irep_2022_closing_the_loop

db88bd3ead2231636aa46e36f0a0272b17437612

[ "MIT" ]

null

# __init__.py from .NSWPH_functions import NSWPH_Initialize_Nm1_Models, NSWPH_Minimum_Data_Point, NSWPH_Directed_Walk_Data from .create_datasets import evaluate_input_OPs

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010ad8eaef72dca84f9bb42e48848a8fa78cc183

111

py

Python

config.py

RomaOkorosso/fes-test-task

cfd8212dfbc9b2b0669ce6e1ea0a59b3f96809dc

[ "MIT" ]

null

config.py

RomaOkorosso/fes-test-task

cfd8212dfbc9b2b0669ce6e1ea0a59b3f96809dc

[ "MIT" ]

null

config.py

RomaOkorosso/fes-test-task

cfd8212dfbc9b2b0669ce6e1ea0a59b3f96809dc

[ "MIT" ]

null

# created by RomaOkorosso at 21.03.2021 # config.py db_url = "postgres://USER:PASSWORD@IP:PORT/DATABASE_NAME"

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5

012c203c1d4459b2909816795351727c39e6834b

39

py

Python

onebarangay_psql/rbi/tests/__init__.py

PrynsTag/oneBarangay-PostgreSQL

11d7b97b57603f4c88948905560a22a5314409ce

[ "Apache-2.0" ]

null

onebarangay_psql/rbi/tests/__init__.py

PrynsTag/oneBarangay-PostgreSQL

11d7b97b57603f4c88948905560a22a5314409ce

[ "Apache-2.0" ]

43

2022-02-07T00:18:35.000Z

2022-03-21T04:42:48.000Z

onebarangay_psql/rbi/tests/__init__.py

PrynsTag/oneBarangay-PostgreSQL

11d7b97b57603f4c88948905560a22a5314409ce

[ "Apache-2.0" ]

null

"""Default init file for rbi tests."""

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013e4a460398c400c9de86df39f0cac5a3303a39

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py

Python

conkit/misc/tests/test_bandwidth.py

mesdaghi/conkit

01468761352bd3ac5078e5e9fef6f73c8c49036e

[ "BSD-3-Clause" ]

12

2017-06-12T17:20:32.000Z

2021-12-10T09:35:26.000Z

conkit/misc/tests/test_bandwidth.py

mesdaghi/conkit

01468761352bd3ac5078e5e9fef6f73c8c49036e

[ "BSD-3-Clause" ]

60

2017-02-08T19:29:34.000Z

2022-03-17T16:00:54.000Z

conkit/misc/tests/test_bandwidth.py

mesdaghi/conkit

01468761352bd3ac5078e5e9fef6f73c8c49036e

[ "BSD-3-Clause" ]

12

2017-09-25T07:25:35.000Z

2022-02-27T18:59:13.000Z

"""Testing facility for conkit.misc.bandwidth""" __author__ = "Felix Simkovic" __date__ = "19 Jun 2017" import numpy as np import unittest from conkit.misc import bandwidth from conkit.misc.ext import c_bandwidth class TestAmiseBW(unittest.TestCase): def test_bandwidth_1(self): xy = np.array([(1, 5), (3, 3), (2, 4)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.AmiseBW(x).bandwidth, 7), 1.1455243) def test_bandwidth_2(self): xy = np.array([(1, 5), (3, 3), (2, 4), (1, 10), (4, 9)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.AmiseBW(x).bandwidth, 7), 1.5310027) def test_bandwidth_3(self): xy = np.array([(3, 5), (2, 4), (3, 4)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.AmiseBW(x).bandwidth, 7), 0.3758801) class TestBowmanBW(unittest.TestCase): def test_bandwidth_1(self): xy = np.array([(1, 5), (3, 3), (2, 4)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.BowmanBW(x).bandwidth, 7), 0.7881495) def test_bandwidth_2(self): xy = np.array([(1, 5), (3, 3), (2, 4), (1, 10), (4, 9)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.BowmanBW(x).bandwidth, 7), 1.4223373) def test_bandwidth_3(self): xy = np.array([(3, 5), (2, 4), (3, 4)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.BowmanBW(x).bandwidth, 7), 0.6052020) class TestLinearBW(unittest.TestCase): def test_bandwidth_1(self): xy = np.array([(1, 5), (3, 3), (2, 4)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(bandwidth.LinearBW(x, threshold=8).bandwidth, 0.625) def test_bandwidth_2(self): xy = np.array([(1, 5), (3, 3), (2, 4), (1, 10), (4, 9)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(bandwidth.LinearBW(x, threshold=10).bandwidth, 1.0) def test_bandwidth_3(self): xy = np.array([(3, 5), (2, 4), (3, 4)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.LinearBW(x, threshold=15).bandwidth, 7), 0.3333333) class TestScottBW(unittest.TestCase): def test_bandwidth_1(self): xy = np.array([(1, 5), (3, 3), (2, 4)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.ScottBW(x).bandwidth, 7), 0.8357821) def test_bandwidth_2(self): xy = np.array([(1, 5), (3, 3), (2, 4), (1, 10), (4, 9)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.ScottBW(x).bandwidth, 7), 1.4513602) def test_bandwidth_3(self): xy = np.array([(3, 5), (2, 4), (3, 4)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.ScottBW(x).bandwidth, 7), 0.5179240) class TestSilvermanBW(unittest.TestCase): def test_bandwidth_1(self): xy = np.array([(1, 5), (3, 3), (2, 4)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.SilvermanBW(x).bandwidth, 7), 0.7523629) def test_bandwidth_2(self): xy = np.array([(1, 5), (3, 3), (2, 4), (1, 10), (4, 9)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.SilvermanBW(x).bandwidth, 7), 1.3065002) def test_bandwidth_3(self): xy = np.array([(3, 5), (2, 4), (3, 4)], dtype=np.int64) x = np.asarray([i for (x, y) in xy for i in np.arange(x, y + 1)])[:, np.newaxis] self.assertEqual(round(bandwidth.SilvermanBW(x).bandwidth, 7), 0.4662301) class Test(unittest.TestCase): def test_bandwidth_factory_1(self): obj = bandwidth.bandwidth_factory("amise") self.assertEqual(str(obj), "<class 'conkit.misc.bandwidth.AmiseBW'>") def test_bandwidth_factory_2(self): obj = bandwidth.bandwidth_factory("bowman") self.assertEqual(str(obj), "<class 'conkit.misc.bandwidth.BowmanBW'>") def test_bandwidth_factory_3(self): obj = bandwidth.bandwidth_factory("linear") self.assertEqual(str(obj), "<class 'conkit.misc.bandwidth.LinearBW'>") def test_bandwidth_factory_4(self): obj = bandwidth.bandwidth_factory("scott") self.assertEqual(str(obj), "<class 'conkit.misc.bandwidth.ScottBW'>") def test_bandwidth_factory_5(self): obj = bandwidth.bandwidth_factory("silverman") self.assertEqual(str(obj), "<class 'conkit.misc.bandwidth.SilvermanBW'>") def test_bandwidth_factory_6(self): with self.assertRaises(ValueError): bandwidth.bandwidth_factory("SILVERMAN") def test_bandwidth_factory_7(self): with self.assertRaises(ValueError): bandwidth.bandwidth_factory("Silverman") def test_bandwidth_factory_8(self): with self.assertRaises(ValueError): bandwidth.bandwidth_factory("silvermn") def test_bandwidth_factory_9(self): with self.assertRaises(ValueError): bandwidth.bandwidth_factory("garbage") class TestExt(unittest.TestCase): def test_gauss_curvature_1(self): A = np.array([[1], [2], [3], [4], [5], [3], [2], [3], [4]], dtype=np.int64) curvature = c_bandwidth.c_get_gauss_curvature(A, -1.5, 0.5) self.assertAlmostEqual(3.171746247735917e-05, curvature) def test_gauss_curvature_2(self): A = np.array([[1]], dtype=np.int64) curvature = c_bandwidth.c_get_gauss_curvature(A, -1.5, 0.5) self.assertAlmostEqual(0.0002854501468289852, curvature) def test_gauss_curvature_3(self): A = np.array([[1]], dtype=np.int64) curvature = c_bandwidth.c_get_gauss_curvature(A, 0, 0.5) self.assertAlmostEqual(1.2957831963165134, curvature) def test_stiffness_integral_1(self): A = np.array([[1], [2], [3], [4], [5], [3], [2], [3], [4]], dtype=np.int64) stiff_integ = c_bandwidth.c_get_stiffness_integral(A, 2.0, 0.0001) self.assertAlmostEqual(0.003100864697366348, stiff_integ) def test_stiffness_integral_2(self): A = np.array([[1], [2], [3], [4], [5], [3], [2], [3], [4]], dtype=np.int64) stiff_integ = c_bandwidth.c_get_stiffness_integral(A, 2.0, 0.1) self.assertAlmostEqual(0.003100864697366348, stiff_integ) def test_stiffness_integral_3(self): A = np.array([[1], [2], [3], [4], [5], [3], [2], [3], [4]], dtype=np.int64) stiff_integ = c_bandwidth.c_get_stiffness_integral(A, 1000.0, 0.0001) self.assertAlmostEqual(2.1106164693083826e-16, stiff_integ) def test_optimize_bandwidth_1(self): A = np.array([[1], [2], [3], [4], [5], [3], [2], [3], [4]], dtype=np.int64) optimized = c_bandwidth.c_optimize_bandwidth(A, 2.0) self.assertAlmostEqual(0.4116948343202962, optimized) def test_optimize_bandwidth_2(self): A = np.array([[1], [2], [3], [4], [5], [3], [2], [3], [4]], dtype=np.int64) optimized = c_bandwidth.c_optimize_bandwidth(A, 1000.0) self.assertAlmostEqual(317.11331138268406, optimized) if __name__ == "__main__": unittest.main(verbosity=2)

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Aimini/51cpu

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script/instructions/__init__.py

Aimini/51cpu

cdeb75510d1dcd867fbebe10e963c4dbecd5ff13

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script/instructions/__init__.py

Aimini/51cpu

cdeb75510d1dcd867fbebe10e963c4dbecd5ff13

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clean-example.py

xflr6/latexpages

65d2961ecbbf47ab1ab126cab90b63e1ba121e26

[ "MIT" ]

2

2019-05-19T00:08:10.000Z

2021-03-29T14:10:25.000Z

clean-example.py

xflr6/latexpages

65d2961ecbbf47ab1ab126cab90b63e1ba121e26

[ "MIT" ]

null

clean-example.py

xflr6/latexpages

65d2961ecbbf47ab1ab126cab90b63e1ba121e26

[ "MIT" ]

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2021-03-29T14:14:18.000Z

#!/usr/bin/env python3 # clean-example.py import latexpages if __name__ == '__main__': latexpages.clean('example/latexpages.ini')

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Python

home/pedrosenarego/scripts/zorba/gestures/armsinside.py

rv8flyboy/pyrobotlab

4e04fb751614a5cb6044ea15dcfcf885db8be65a

[ "Apache-2.0" ]

63

2015-02-03T18:49:43.000Z

2022-03-29T03:52:24.000Z

home/pedrosenarego/scripts/zorba/gestures/armsinside.py

rv8flyboy/pyrobotlab

4e04fb751614a5cb6044ea15dcfcf885db8be65a

[ "Apache-2.0" ]

16

2016-01-26T19:13:29.000Z

2018-11-25T21:20:51.000Z

home/pedrosenarego/scripts/zorba/gestures/armsinside.py

rv8flyboy/pyrobotlab

4e04fb751614a5cb6044ea15dcfcf885db8be65a

[ "Apache-2.0" ]

151

2015-01-03T18:55:54.000Z

2022-03-04T07:04:23.000Z

def armsinside(): i01.rightArm.rotate.attach() i01.rightArm.rotate.moveTo(0) sleep(7) i01.rightArm.rotate.detach()

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py

Python

src/api/__init__.py

MrPingouinMC/Amulet-Map-Editor

7fe0d16a58875e718d2a6ca90752e9ff72bf2173

[ "MIT" ]

1

2021-11-12T01:26:06.000Z

src/api/__init__.py

MrPingouinMC/Amulet-Map-Editor

7fe0d16a58875e718d2a6ca90752e9ff72bf2173

[ "MIT" ]

null

src/api/__init__.py

MrPingouinMC/Amulet-Map-Editor

7fe0d16a58875e718d2a6ca90752e9ff72bf2173

[ "MIT" ]

null

from api.world import WorldFormat

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py

Python

test/test_devices_page_all_of.py

CiscoDevNet/python-msx-sdk

d7e0a08c656504b4f4551d263e67c671a2a04b3f

[ "MIT" ]

null

test/test_devices_page_all_of.py

CiscoDevNet/python-msx-sdk

d7e0a08c656504b4f4551d263e67c671a2a04b3f

[ "MIT" ]

null

test/test_devices_page_all_of.py

CiscoDevNet/python-msx-sdk

d7e0a08c656504b4f4551d263e67c671a2a04b3f

[ "MIT" ]

null

""" MSX SDK MSX SDK client. # noqa: E501 The version of the OpenAPI document: 1.0.9 Generated by: https://openapi-generator.tech """ import sys import unittest import python_msx_sdk from python_msx_sdk.model.device import Device globals()['Device'] = Device from python_msx_sdk.model.devices_page_all_of import DevicesPageAllOf class TestDevicesPageAllOf(unittest.TestCase): """DevicesPageAllOf unit test stubs""" def setUp(self): pass def tearDown(self): pass def testDevicesPageAllOf(self): """Test DevicesPageAllOf""" # FIXME: construct object with mandatory attributes with example values # model = DevicesPageAllOf() # noqa: E501 pass if __name__ == '__main__': unittest.main()

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Python

test-cr-client/testfiles/bad_test.py

Nick-Anderssohn/hello-class

5f9c6ab7a7383d876680e4c3989327ebdda5d2e2

[ "MIT" ]

1

2017-06-06T04:37:34.000Z

test-cr-client/testfiles/bad_test.py

Nick-Anderssohn/hello-compsci

5f9c6ab7a7383d876680e4c3989327ebdda5d2e2

[ "MIT" ]

1

2017-07-27T01:57:57.000Z

test-cr-client/testfiles/bad_test.py

Nick-Anderssohn/hello-compsci

5f9c6ab7a7383d876680e4c3989327ebdda5d2e2

[ "MIT" ]

null

prit("Hello Python3!")

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Python

enthought/chaco/datamapper.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

3

2016-12-09T06:05:18.000Z

2018-03-01T13:00:29.000Z

enthought/chaco/datamapper.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

1

2020-12-02T00:51:32.000Z

2020-12-02T08:48:55.000Z

enthought/chaco/datamapper.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

null

# proxy module from __future__ import absolute_import from chaco.datamapper import *

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Python

replication/runtime_analysis_graph2vec_geo2dr.py

paulmorio/geo2dr

49d5f1cdc0a4aa0c2c19744f6b1c723fd5988955

[ "MIT" ]

32

2020-03-13T21:09:50.000Z

2021-10-02T13:01:46.000Z

replication/runtime_analysis_graph2vec_geo2dr.py

paulmorio/geo2dr

49d5f1cdc0a4aa0c2c19744f6b1c723fd5988955

[ "MIT" ]

3

2020-03-22T14:34:49.000Z

2021-08-17T15:20:40.000Z

replication/runtime_analysis_graph2vec_geo2dr.py

paulmorio/geo2dr

49d5f1cdc0a4aa0c2c19744f6b1c723fd5988955

[ "MIT" ]

5

2020-03-29T00:31:10.000Z

2021-08-17T10:57:32.000Z

""" A script which times the training time of our graph2vec reimplementations using both disk memory dataset loaders and ram memory dataset loaders. """ import os import time import numpy as np from geometric2dr.decomposition.weisfeiler_lehman_patterns import wl_corpus from geometric2dr.embedding_methods.pvdbow_trainer import Trainer, InMemoryTrainer from geometric2dr.embedding_methods.classify import cross_val_accuracy import geometric2dr.embedding_methods.utils as utils # Input data paths dataset = "MUTAG" corpus_data_dir = "data/" + dataset wl_depth = 2 min_count = 0 emb_dimension = 128 batch_size = 1024 epochs = 100 initial_lr = 0.1 # Learn embeddings graph_files = utils.get_files(corpus_data_dir, ".gexf", max_files=0) wl_corpus(graph_files, wl_depth) extension = ".wld" + str(wl_depth) # Extension of the graph document output_embedding_fh = "runtime_analysis_embeddings" # Load from disk trainer hd_times = [] for _ in range(10): trainer = Trainer(corpus_dir=corpus_data_dir, extension=extension, max_files=0, output_fh=output_embedding_fh, emb_dimension=emb_dimension, batch_size=batch_size, epochs=epochs, initial_lr=initial_lr, min_count=min_count) start_time = time.time() trainer.train() end_time = (time.time() - start_time) hd_times.append(end_time) mean_hd_time = np.mean(hd_times) std_hd_time = np.std(hd_times) # Use memory trainer memory_times = [] for _ in range(10): trainer = InMemoryTrainer(corpus_dir=corpus_data_dir, extension=extension, max_files=0, output_fh=output_embedding_fh, emb_dimension=emb_dimension, batch_size=batch_size, epochs=epochs, initial_lr=initial_lr, min_count=min_count) start_time = time.time() trainer.train() end_time = (time.time() - start_time) memory_times.append(end_time) mean_mem_time = np.mean(memory_times) std_mem_time = np.std(memory_times) # print("Hard Drive Geo2DR Graph2Vec mean time: %.4f standard dev: %.4f " % (mean_hd_time, std_hd_time)) print("In Memory Geo2DR Graph2Vec mean time: %.4f standard dev: %.4f " % (mean_mem_time, std_mem_time)) # Anonymous Walk Embeddings import os import time import numpy as np import geometric2dr.embedding_methods.utils as utils from geometric2dr.decomposition.anonymous_walk_patterns import awe_corpus from geometric2dr.embedding_methods.classify import cross_val_accuracy from geometric2dr.embedding_methods.pvdm_trainer import PVDM_Trainer # Note use of PVDM aw_length = 10 label_setting = "nodes" # AWE is quite nice and versatile allowing for different node-label/edge-label settings # Input data paths dataset = "MUTAG" corpus_data_dir = "data/" + dataset # Desired output paths output_embedding_fh = "AWE_Embeddings.json" ####### # Step 1 Create corpus data for neural language model # We keep permanent files for sake of deeper post studies and testing ####### graph_files = utils.get_files(corpus_data_dir, ".gexf", max_files=0) memory_times = [] for _ in range(10): awe_corpus(corpus_data_dir, aw_length, label_setting, saving_graph_docs=True) extension = ".awe_" + str(aw_length) + "_" + label_setting ###### # Step 2 Train a neural language model to learn distributed representations # of the graphs directly or of its substructures. Here we learn it directly # for an example of the latter check out the DGK models. ###### trainer = PVDM_Trainer(corpus_dir=corpus_data_dir, extension=extension, max_files=0, window_size=16, output_fh=output_embedding_fh, emb_dimension=128, batch_size=100, epochs=100, initial_lr=0.1, min_count=0) start_time = time.time() trainer.train() end_time = (time.time() - start_time) memory_times.append(end_time) mean_mem_time = np.mean(memory_times) std_mem_time = np.std(memory_times) print("In Memory Geo2DR AWE-DD mean time: %.4f standard dev: %.4f " % (mean_mem_time, std_mem_time)) import os import time import numpy as np import geometric2dr.embedding_methods.utils as utils from geometric2dr.decomposition.weisfeiler_lehman_patterns import wl_corpus from geometric2dr.embedding_methods.skipgram_trainer import InMemoryTrainer # DGK-WL # Input data paths dataset = "MUTAG" corpus_data_dir = "data/" + dataset # Desired output paths for subgraph embeddings output_embedding_fh = "WL_Subgraph_Embeddings.json" # WL decomposition hyperparameters wl_depth = 2 ############ # Step 1 # Run the decomposition algorithm to get subgraph patterns across the graphs of MUTAG ############ graph_files = utils.get_files(corpus_data_dir, ".gexf", max_files=0) corpus, vocabulary, prob_map, num_graphs, graph_map = wl_corpus(graph_files, wl_depth) extension = ".wld" + str(wl_depth) # Extension of the graph document ############ # Step 2 # Train a skipgram (w. Negative Sampling) model to learn distributed representations of the subgraph patterns ############ memory_times = [] for _ in range(10): trainer = InMemoryTrainer(corpus_dir=corpus_data_dir, extension=extension, max_files=0, window_size=10, output_fh=output_embedding_fh, emb_dimension=32, batch_size=1280, epochs=100, initial_lr=0.1, min_count=1) start_time = time.time() trainer.train() end_time = (time.time() - start_time) memory_times.append(end_time) mean_mem_time = np.mean(memory_times) std_mem_time = np.std(memory_times) print("In Memory Geo2DR DGK-WL mean time: %.4f standard dev: %.4f " % (mean_mem_time, std_mem_time)) # DGK-SP import os import time import numpy as np import geometric2dr.embedding_methods.utils as utils from geometric2dr.decomposition.shortest_path_patterns import sp_corpus from geometric2dr.embedding_methods.skipgram_trainer import InMemoryTrainer # Input data paths dataset = "MUTAG" corpus_data_dir = "data/" + dataset # Desired output paths for subgraph embeddings output_embedding_fh = "SPP_Subgraph_Embeddings.json" ############ # Step 1 # Run the decomposition algorithm to get subgraph patterns across the graphs of MUTAG ############ graph_files = utils.get_files(corpus_data_dir, ".gexf", max_files=0) corpus, vocabulary, prob_map, num_graphs, graph_map = sp_corpus(corpus_data_dir) # will produce .spp files extension = ".spp" ############ # Step 2 # Train a skipgram (w. Negative Sampling) model to learn distributed representations of the subgraph patterns ############ memory_times = [] for _ in range(10): trainer = InMemoryTrainer(corpus_dir=corpus_data_dir, extension=extension, max_files=0, window_size=10, output_fh=output_embedding_fh, emb_dimension=32, batch_size=128, epochs=100, initial_lr=0.1, min_count=1) start_time = time.time() trainer.train() end_time = (time.time() - start_time) memory_times.append(end_time) mean_mem_time = np.mean(memory_times) std_mem_time = np.std(memory_times) print("In Memory Geo2DR DGK-SP mean time: %.4f standard dev: %.4f " % (mean_mem_time, std_mem_time)) # # DGK-GK import os import time import numpy as np import geometric2dr.embedding_methods.utils as utils from geometric2dr.decomposition.graphlet_patterns import graphlet_corpus from geometric2dr.embedding_methods.skipgram_trainer import Trainer, InMemoryTrainer # Input data paths dataset = "MUTAG" corpus_data_dir = "data/" + dataset # Desired output paths for subgraph embeddings output_embedding_fh = "Graphlet_Subgraph_Embeddings.json" # Graphlet decomposition hyperparameters num_graphlet = 7 # size of the graphlets to extract sample_size = 100 # number of graphlets samples to extract ############ # Step 1 # Run the decomposition algorithm to get subgraph patterns across the graphs of MUTAG ############ graph_files = utils.get_files(corpus_data_dir, ".gexf", max_files=0) corpus, vocabulary, prob_map, num_graphs, graph_map = graphlet_corpus(corpus_data_dir, num_graphlet, sample_size) extension = ".graphlet_ng_"+str(num_graphlet)+"_ss_"+str(sample_size) ############ # Step 2 # Train a skipgram (w. Negative Sampling) model to learn distributed representations of the subgraph patterns ############ memory_times = [] for _ in range(10): trainer = InMemoryTrainer(corpus_dir=corpus_data_dir, extension=extension, max_files=0, window_size=10, output_fh=output_embedding_fh, emb_dimension=32, batch_size=128, epochs=100, initial_lr=0.1, min_count=0) start_time = time.time() trainer.train() end_time = (time.time() - start_time) memory_times.append(end_time) mean_mem_time = np.mean(memory_times) std_mem_time = np.std(memory_times) print("In Memory Geo2DR DGK-GRAPHLET mean time: %.4f standard dev: %.4f " % (mean_mem_time, std_mem_time))

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149

py

Python

__init__.py

mawanda-jun/TReNDS-neuroimaging

8075f4196e7eb812ce96b5a10b18d13c293ce727

[ "MIT" ]

1

2020-06-28T18:13:49.000Z

__init__.py

mawanda-jun/TReNDS-neuroimaging

8075f4196e7eb812ce96b5a10b18d13c293ce727

[ "MIT" ]

null

__init__.py

mawanda-jun/TReNDS-neuroimaging

8075f4196e7eb812ce96b5a10b18d13c293ce727

[ "MIT" ]

1

2022-03-18T13:13:10.000Z

from dataset import TReNDS_dataset from network import ShallowNet from pytorchtools import EarlyStopping, TReNDSLoss from vae_classifier import Model

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py

Python

niyopolymers/patches/create_warning_letter_template.py

venku31/niyopolymers

f150ee591d2ea10720d8e98c5f6abf7c6e2edb2d

[ "MIT" ]

null

niyopolymers/patches/create_warning_letter_template.py

venku31/niyopolymers

f150ee591d2ea10720d8e98c5f6abf7c6e2edb2d

[ "MIT" ]

null

niyopolymers/patches/create_warning_letter_template.py

venku31/niyopolymers

f150ee591d2ea10720d8e98c5f6abf7c6e2edb2d

[ "MIT" ]

null

import frappe def execute(): path = frappe.get_app_path("niyopolymers", "patches", "imports", "warning_letter_template.csv") frappe.core.doctype.data_import.data_import.import_file("Warning Letter Template", path, "Insert", console=True)

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61d781493e7ab1c07e72e52880da7d17e717503c

34

py

Python

ptop/statistics/__init__.py

deeps-nars/ptop

96822e8c8ecb2fcce1b0edf975266985af4d16e4

[ "MIT" ]

327

2015-07-07T14:18:07.000Z

2017-06-19T21:53:32.000Z

ptop/statistics/__init__.py

deeps-nars/ptop

96822e8c8ecb2fcce1b0edf975266985af4d16e4

[ "MIT" ]

47

2017-07-12T12:24:20.000Z

2021-07-02T20:49:46.000Z

ptop/statistics/__init__.py

deeps-nars/ptop

96822e8c8ecb2fcce1b0edf975266985af4d16e4

[ "MIT" ]

40

2017-11-22T06:12:33.000Z

2021-11-20T01:48:37.000Z

from .statistics import Statistics

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61d953e246348a46d0d6759a146f02216a0d15d0

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py

Python

symtmm/__init__.py

Matael/symtmm

7156172259c77b3fa48df322f3456313c1031fcd

[ "MIT" ]

1

2021-02-24T01:53:57.000Z

symtmm/__init__.py

Matael/symtmm

7156172259c77b3fa48df322f3456313c1031fcd

[ "MIT" ]

null

symtmm/__init__.py

Matael/symtmm

7156172259c77b3fa48df322f3456313c1031fcd

[ "MIT" ]

null

__VERSION__ = '0.0' from symtmm.solver import Solver from symtmm.layers import Layer from symtmm.media import Air, Eqf

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5

61e92e63ec1728daa5401b0ab36092e1b6049f1d

113

py

Python

setup.py

yespon/Chinese-Annotator

79aca8b0428a48ac789f2d2771e9e9fb03ccc8fa

[ "Apache-2.0" ]

915

2018-07-25T07:30:27.000Z

2022-03-25T14:09:17.000Z

setup.py

12xiaoni/data-label

448a22941d9c4a55c7756003d94e410c2506ec43

[ "Apache-2.0" ]

20

2018-10-12T15:48:56.000Z

2021-09-27T09:12:01.000Z

setup.py

12xiaoni/data-label

448a22941d9c4a55c7756003d94e410c2506ec43

[ "Apache-2.0" ]

204

2018-07-30T06:52:29.000Z

2022-03-03T15:18:39.000Z

from setuptools import setup, find_packages setup(name='chi_annotator', version='1.0', packages=find_packages())

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61f15454ed7e3843b25bdc56e3c3d0bd9f563c46

97

py

Python

demodocusfw/graph/__init__.py

dchud/demodocus

e37040af521bc56a61fea6327fae111268b81497

[ "Apache-2.0" ]

7

2020-11-17T15:02:32.000Z

2022-02-18T23:53:23.000Z

demodocusfw/graph/__init__.py

dchud/demodocus

e37040af521bc56a61fea6327fae111268b81497

[ "Apache-2.0" ]

20

2020-11-02T13:40:40.000Z

2020-11-30T14:09:01.000Z

demodocusfw/graph/__init__.py

dchud/demodocus

e37040af521bc56a61fea6327fae111268b81497

[ "Apache-2.0" ]

4

2020-11-02T18:48:24.000Z

2020-11-20T18:31:29.000Z

from .state import State, StateData from .edge import Edge, EdgeMetrics from .graph import Graph

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113d6b738ba44f91f808dbc7223d27a629d55dc0

324

py

Python

5. Logistic Regression/accessory_fun.py

haitaozhao/PRSL

c81d64d1d2968af8ba5f34ce0ecfed32007822f1

[ "MIT" ]

5

2022-02-27T08:35:44.000Z

2022-03-12T07:53:53.000Z

5. Logistic Regression/accessory_fun.py

haitaozhao/PRSL

c81d64d1d2968af8ba5f34ce0ecfed32007822f1

[ "MIT" ]

null

5. Logistic Regression/accessory_fun.py

haitaozhao/PRSL

c81d64d1d2968af8ba5f34ce0ecfed32007822f1

[ "MIT" ]

null

import numpy as np # sigmoid function def my_sigmoid(w,x): return 1/(1+np.exp(-w.T.dot(x.T))) # 损失函数 def obj_fun(w,x,y): tmp = y.reshape(1,-1)*np.log(my_sigmoid(w,x)) + \ (1-y.reshape(1,-1))*np.log(1-my_sigmoid(w,x)) return np.sum(-tmp) # 计算随机梯度的函数 def my_Stgrad(w,x,y): return (my_sigmoid(w,x) - y)*x.T

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114e66a6e7250ae3d47a7f2f3dd3934b10cb8681

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py

Python

smwds/user/__init__.py

rtx3/Salt-MWDS

33d8b0abe65c74fba1a7be6838575603983c6c43

[ "MIT" ]

2

2016-08-26T06:20:04.000Z

2016-08-26T12:50:02.000Z

smwds/user/__init__.py

rtx3/Salt-MWDS

33d8b0abe65c74fba1a7be6838575603983c6c43

[ "MIT" ]

null

smwds/user/__init__.py

rtx3/Salt-MWDS

33d8b0abe65c74fba1a7be6838575603983c6c43

[ "MIT" ]

1

2017-03-31T05:20:10.000Z

# -*- coding: utf-8 -*- from user.models import User from user.views import user

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115edd329a78a1257c5b50e9f817642feb21777f

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py

Python

zeitslots_to_json.py

omehling/faim_website

0131c834dc6e653ce5c890723b433a43bb1628b9

[ "MIT" ]

null

zeitslots_to_json.py

omehling/faim_website

0131c834dc6e653ce5c890723b433a43bb1628b9

[ "MIT" ]

null

zeitslots_to_json.py

omehling/faim_website

0131c834dc6e653ce5c890723b433a43bb1628b9

[ "MIT" ]

null

import pandas as pd dfcsv=pd.read_csv('gruppen-zeitslots-vers3.csv') dfcsv.T.to_json('gruppen-zeitslots.json')

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null

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1

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5

116186ae2711713c8d5d1eecadd63b1e51735895

17

py

Python

nilm_metadata/central_metadata/appliance_types/__init__.py

BaluJr/nilm_metadata

3a498e3acd0975e6d77e68887a0119c51b74b9d7

[ "Apache-2.0" ]

null

nilm_metadata/central_metadata/appliance_types/__init__.py

BaluJr/nilm_metadata

3a498e3acd0975e6d77e68887a0119c51b74b9d7

[ "Apache-2.0" ]

null

nilm_metadata/central_metadata/appliance_types/__init__.py

BaluJr/nilm_metadata

3a498e3acd0975e6d77e68887a0119c51b74b9d7

[ "Apache-2.0" ]

null

#print "HERE too"

17

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1

17

0.8

0.941176

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true

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0

1

0

1

0

null

0

1

0

5

feccd72bcb5fa1af7f5f738acc1bad2200e60457

86

py

Python

xremotebot/lib/exceptions.py

Robots-Linti/xremotebot

f07b65e1d3e1698ad330445fadb3da95198282c9

[ "MIT" ]

null

xremotebot/lib/exceptions.py

Robots-Linti/xremotebot

f07b65e1d3e1698ad330445fadb3da95198282c9

[ "MIT" ]

null

xremotebot/lib/exceptions.py

Robots-Linti/xremotebot

f07b65e1d3e1698ad330445fadb3da95198282c9

[ "MIT" ]

null

class NoFreeRobots(Exception): pass class UnavailableRobot(Exception): pass

12.285714

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true

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null

0

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5

3a1c1f915d35575f726b94cb0bfeef7f349d82b3

42

py

Python

global_id/models/mixins/__init__.py

ThePokerFaCcCe/messenger

2db3d5c2ccd05ac40d2442a13d664ca9ad3cb14c

[ "MIT" ]

null

global_id/models/mixins/__init__.py

ThePokerFaCcCe/messenger

2db3d5c2ccd05ac40d2442a13d664ca9ad3cb14c

[ "MIT" ]

null

global_id/models/mixins/__init__.py

ThePokerFaCcCe/messenger

2db3d5c2ccd05ac40d2442a13d664ca9ad3cb14c

[ "MIT" ]

null

from .guid_generic_mixin import GUIDMixin

21

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1

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42

1

42

0.921053

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0

null

0

1

0

1

0

5

3a4da97c089e00efe5f69ba2912a4ba255a5d6f0

3,624

py

Python

tests/test_gpuctl.py

Ed-Yang/gpuctl

c84dd38d6732ce882a099d952bd2f519dd87c292

[ "MIT" ]

2

2021-03-24T13:57:33.000Z

2021-05-11T00:58:28.000Z

tests/test_gpuctl.py

Ed-Yang/gpuctl

c84dd38d6732ce882a099d952bd2f519dd87c292

[ "MIT" ]

null

tests/test_gpuctl.py

Ed-Yang/gpuctl

c84dd38d6732ce882a099d952bd2f519dd87c292

[ "MIT" ]

null

#!/usr/bin/env python3 import time # from re import U import unittest from gpuctl import PciDev, GpuCtl, GpuDev, GpuAMD, GpuNV, GpuOk from gpuctl import GpuOk, GpuNak class TestGpuCtl(unittest.TestCase): def test_invalid_key(self): gpu_ctl = None try: gpu_ctl = GpuCtl(slots='aaaa') self.assertEqual(gpu_ctl, None) except: pass def test_discover_all(self): pci_devices = PciDev.discovery() gpu_devices = [] for pdev in pci_devices: gpu = None if pdev.is_amd(): gpu = GpuAMD(pdev) if pdev.is_nvidia(): gpu = GpuNV(pdev) if gpu and gpu.is_gpu(): gpu_devices.append(gpu) gpu_ctl = GpuCtl(gpu_devices=gpu_devices) def test_discover_vendor(self): vendors = ['AMD', 'NVIDIA'] pci_devices = PciDev.discovery(vendor_filter=vendors) gpu_devices = [] for pdev in pci_devices: gpu = None if pdev.is_amd(): gpu = GpuAMD(pdev) if pdev.is_nvidia(): gpu = GpuNV(pdev) if gpu and gpu.is_gpu(): gpu_devices.append(gpu) gpu_ctl = GpuCtl(gpu_devices=gpu_devices) def test_add_devices(self): vendors = ['AMD', 'NVIDIA'] pci_devices = PciDev.discovery(vendor_filter=vendors) gpu_devices = [] for pdev in pci_devices: gpu = None if pdev.is_amd(): gpu = GpuAMD(pdev) if pdev.is_nvidia(): gpu = GpuNV(pdev) if gpu and gpu.is_gpu(): gpu_devices.append(gpu) gpu_ctl = GpuCtl(gpu_devices=gpu_devices) cnt = gpu_ctl.add_gpu_devices(gpu_devices) self.assertEqual(cnt, 0) def test_over_temp(self): slot_name = '1111:11:11.1' pci_id = '1111:1111' pdev = PciDev(slot_name, pci_id, 'mock pci') self.assertIsNotNone(pdev) self.assertEqual(pdev.vendor_name(), 'Other') gpu_dev = GpuNak(pdev) self.assertIsNotNone(gpu_dev) gpu_ctl = GpuCtl(gpu_devices=[gpu_dev], fan=10, temp=20, tas='./tests/ok.sh') self.assertNotEqual(gpu_ctl, None) rv = gpu_ctl.set_interval(wait_period=10) self.assertTrue(rv) gpu_ctl.start() time.sleep(5) gpu_ctl.stop() def test_interval(self): slot_name = '1111:11:11.1' pci_id = '1111:1111' pdev = PciDev(slot_name, pci_id, 'mock pci') self.assertIsNotNone(pdev) self.assertEqual(pdev.vendor_name(), 'Other') gpu_dev = GpuOk(pdev) self.assertIsNotNone(gpu_dev) gpu_ctl = GpuCtl(gpu_devices=[gpu_dev]) rv = gpu_ctl.set_interval(intvl=1, wait_period=3) self.assertTrue(rv) rv = gpu_ctl.set_interval(intvl=2, wait_period=20) self.assertTrue(rv) rv = gpu_ctl.set_interval(intvl=2, wait_period=1) self.assertFalse(rv) def test_nak_gpu(self): slot_name = '1111:11:11.1' pci_id = '1111:1111' pdev = PciDev(slot_name, pci_id, 'mock pci') self.assertIsNotNone(pdev) self.assertEqual(pdev.vendor_name(), 'Other') gpu_dev = GpuNak(pdev) self.assertIsNotNone(gpu_dev) gpu_ctl = GpuCtl(gpu_devices=[gpu_dev], verbose=True) rv = gpu_ctl.set_interval(wait_period=10) self.assertTrue(rv) gpu_ctl.start() time.sleep(5) gpu_ctl.stop() if __name__ == '__main__': unittest.main()

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null

0

1

0

null

0

5

3a5683e4dd15e942657e684e15324a4d78686ef0

17,148

py

Python

scav-hunt/scaveye.py

scottshepard/MScA-Robotics-Capstone

29762ef87274fcd4d86a69918edc44f2a9f99ed5

[ "MIT" ]

3

2019-11-16T20:38:10.000Z

2020-04-11T01:24:36.000Z

scav-hunt/scaveye.py

scottshepard/MScA-Robotics-Capstone

29762ef87274fcd4d86a69918edc44f2a9f99ed5

[ "MIT" ]

1

2019-12-05T01:57:28.000Z

scav-hunt/scaveye.py

MScA-Robotics/capstone-project-3

29762ef87274fcd4d86a69918edc44f2a9f99ed5

[ "MIT" ]

2

2020-05-17T19:56:12.000Z

2020-06-23T02:09:30.000Z

import os import glob import picamera import cv2 import numpy as np import importlib.util from datetime import datetime import videorecorder as vr import time from collections import Counter # If using TPU, need to load a different library # from tensorflow.lite.python.interpreter import Interpreter def take_picture(path): if path is None: path = "/home/pi/Pictures" camera = picamera.PiCamera() try: camera.capture(os.path.join(path, "image_{0}.jpg".format(datetime.now().strftime('%m%d%Y%H%M%S')))) finally: print('Picture taken') camera.close() def record_video(path=None, cone_color='green', duration=5, runid=0): if path is None: path="/home/pi/Videos" path = os.path.join(path,cone_color) try: recorder = vr.VideoRecorder(path,runid) print('Loaded Video Recorder') recorder.start_recording() time.sleep(duration) recorder.stop_recording() except: print('Video Recording failed') finally: print('Video recorded') class ObjectClassificationModel: def __init__(self, model_dir, image_dir, graph_name='detect.tflite', min_conf_threshold=0.5, use_TPU=False): self.model_dir = model_dir self.image_dir = image_dir self.min_conf_threshold = float(min_conf_threshold) self.use_TPU = use_TPU self._load_model(model_dir=model_dir, graph_name=graph_name) def _load_model(self, model_dir, graph_name): CWD_PATH = os.getcwd() # Load model labels PATH_TO_LABELS = os.path.join(CWD_PATH, model_dir, 'labelmap.txt') with open(PATH_TO_LABELS, 'r') as f: labels = [line.strip() for line in f.readlines()] if labels[0] == '???': del(labels[0]) self.labels = labels pkg = importlib.util.find_spec('tensorflow') if pkg is None: from tflite_runtime.interpreter import Interpreter if self.use_TPU: print('Loading tflite interpreter') from tflite_runtime.interpreter import load_delegate else: from tensorflow.lite.python.interpreter import Interpreter if self.use_TPU: print('Loading tflite interpreter') from tflite_runtime.interpreter import load_delegate # If using Edge TPU, assign filename for Edge TPU model if self.use_TPU: # If user has specified the name of the .tflite file, use that name, otherwise use default 'edgetpu.tflite' if (graph_name == 'detect.tflite'): graph_name = 'edgetpu.tflite' PATH_TO_CKPT = os.path.join(CWD_PATH, model_dir, graph_name) # Load the Tensorflow Lite model. # If using Edge TPU, use special load_delegate argument if self.use_TPU: self.interpreter = Interpreter(model_path=PATH_TO_CKPT, experimental_delegates=[load_delegate('libedgetpu.so.1.0')]) print(PATH_TO_CKPT) else: self.interpreter = Interpreter(model_path=PATH_TO_CKPT) self.interpreter.allocate_tensors() # Get model details self.input_details = self.interpreter.get_input_details() self.output_details = self.interpreter.get_output_details() self.height = self.input_details[0]['shape'][1] self.width = self.input_details[0]['shape'][2] self.floating_model = (self.input_details[0]['dtype'] == np.float32) self.input_mean = 127.5 self.input_std = 127.5 def classify(self, image_dir): images = glob.glob(image_dir + '/*') classes_list = [] scores_list = [] for image_path in images: print('Classifying: {}'.format(image_path)) # Load image and resize to expected shape [1xHxWx3] image = cv2.imread(image_path) image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) imH, imW, _ = image.shape image_resized = cv2.resize(image_rgb, (self.width, self.height)) input_data = np.expand_dims(image_resized, axis=0) # Normalize pixel values if using a floating model (i.e. if model is non-quantized) if self.floating_model: input_data = (np.float32(input_data) - self.input_mean) / self.input_std # Perform the actual detection by running the model with the image as input self.interpreter.set_tensor(self.input_details[0]['index'],input_data) self.interpreter.invoke() # Retrieve detection results # We are not using the boxes right now since we do not need to know # where picture the object is, only that it is there. # boxes = interpreter.get_tensor(output_details[0]['index'])[0] # Bounding box coordinates of detected objects classes = self.interpreter.get_tensor(self.output_details[1]['index'])[0] # Class index of detected objects scores = self.interpreter.get_tensor(self.output_details[2]['index'])[0] # Confidence of detected objects classes_list.append(classes[scores > self.min_conf_threshold]) scores_list.append(scores[scores > self.min_conf_threshold]) objects_detected = {} for classes in classes_list: objects = set([self.labels[int(c)] for c in classes]) for obj in objects: if obj in objects_detected.keys(): objects_detected[obj] += 1 else: objects_detected[obj] = 1 return classes_list, scores_list, objects_detected def classify_video(self, video_dir): """Function to detect objects in video file""" #1. Get the list of all video files from the directory passed in videos = glob.glob(video_dir + '/*') #2. Check the number of *.avi files in the folder num_videos = len(videos) #3. Do not run classification if number of videos in the folder are more than 10 and alert if num_videos > 10: print('Found more than 10 videos in the directory: {}'.format(video_dir)) return #4. For each video file for video_file in videos: video_name=os.path.basename(video_file) print('Processing video: {}'.format(video_name)) #4.1 Open the video file video = cv2.VideoCapture(video_file) imW = video.get(cv2.CAP_PROP_FRAME_WIDTH) imH = video.get(cv2.CAP_PROP_FRAME_HEIGHT) collect_labels = [] #4 .1.1 pass frame by frame to the detection model index = 0 print('Min Threshold',self.min_conf_threshold) while(video.isOpened()): # Acquire frame and resize to expected shape [1xHxWx3] ret, frame = video.read() if frame is None: break frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) frame_resized = cv2.resize(frame_rgb, (self.width, self.height)) input_data = np.expand_dims(frame_resized, axis=0) # Normalize pixel values if using a floating model (i.e. if model is non-quantized) if self.floating_model: input_data = (np.float32(input_data) - self.input_mean) / self.input_std # Perform the actual detection by running the model with the image as input self.interpreter.set_tensor(self.input_details[0]['index'],input_data) self.interpreter.invoke() # Retrieve detection results boxes = self.interpreter.get_tensor(self.output_details[0]['index'])[0] # Bounding box coordinates of detected objects classes = self.interpreter.get_tensor(self.output_details[1]['index'])[0] # Class index of detected objects scores = self.interpreter.get_tensor(self.output_details[2]['index'])[0] # Confidence of detected objects # Loop over all detections and draw detection box if confidence is above minimum threshold for i in range(len(scores)): if ((scores[i] > self.min_conf_threshold) and (scores[i] <= 1.0)): # Get bounding box coordinates and draw box # Interpreter can return coordinates that are outside of image dimensions, need to force them to be within image using max() and min() ymin = int(max(1,(boxes[i][0] * imH))) xmin = int(max(1,(boxes[i][1] * imW))) ymax = int(min(imH,(boxes[i][2] * imH))) xmax = int(min(imW,(boxes[i][3] * imW))) cv2.rectangle(frame, (xmin,ymin), (xmax,ymax), (10, 255, 0), 4) # Draw label object_name = self.labels[int(classes[i])] # Look up object name from "labels" array using class index label = '%s: %d%%' % (object_name, int(scores[i]*100)) # Example: 'person: 72%' labelSize, baseLine = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.7, 2) # Get font size label_ymin = max(ymin, labelSize[1] + 10) # Make sure not to draw label too close to top of window cv2.rectangle(frame, (xmin, label_ymin-labelSize[1]-10), (xmin+labelSize[0], label_ymin+baseLine-10), (255, 255, 255), cv2.FILLED) # Draw white box to put label text in cv2.putText(frame, label, (xmin, label_ymin-7), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 0), 2) # Draw label text collect_labels.append(object_name) index += 1 # All the results have been drawn on the frame, so it's time to display it. cv2.imshow('Object detector', frame) video.release() #cv2.destroyAllWindows() if len(collect_labels)>0: most_common,num_most_common = Counter(collect_labels).most_common(1)[0] max_object = most_common else: max_object = 'Nothing' print('Maximum detected object :{}'.format(max_object)) print(Counter(collect_labels)) return max_object class ConeClassificationModel: def __init__(self, model_dir, image_dir, graph_name='cone_detect.tflite', min_conf_threshold=0.5, use_TPU=False): self.model_dir = model_dir self.image_dir = image_dir self.min_conf_threshold = float(min_conf_threshold) self.use_TPU = use_TPU self._load_model(model_dir=model_dir, graph_name=graph_name) def _load_model(self, model_dir, graph_name): CWD_PATH = os.getcwd() # Load model labels PATH_TO_LABELS = os.path.join(CWD_PATH, model_dir, 'labelmap.txt') with open(PATH_TO_LABELS, 'r') as f: labels = [line.strip() for line in f.readlines()] if labels[0] == '???': del(labels[0]) self.labels = labels pkg = importlib.util.find_spec('tensorflow') if pkg is None: from tflite_runtime.interpreter import Interpreter if self.use_TPU: print('Loading tflite interpreter') from tflite_runtime.interpreter import load_delegate else: from tensorflow.lite.python.interpreter import Interpreter if self.use_TPU: print('Loading tflite interpreter') from tflite_runtime.interpreter import load_delegate # If using Edge TPU, assign filename for Edge TPU model if self.use_TPU: # If user has specified the name of the .tflite file, use that name, otherwise use default 'edgetpu.tflite' if (graph_name == 'cone_detect.tflite'): graph_name = 'cone_edgetpu.tflite' # Load the model PATH_TO_CKPT = os.path.join(CWD_PATH, model_dir, graph_name) #self.interpreter = Interpreter(model_path=PATH_TO_CKPT) # Load the Tensorflow Lite model. # If using Edge TPU, use special load_delegate argument if self.use_TPU: self.interpreter = Interpreter(model_path=PATH_TO_CKPT, experimental_delegates=[load_delegate('libedgetpu.so.1.0')]) print(PATH_TO_CKPT) else: self.interpreter = Interpreter(model_path=PATH_TO_CKPT) self.interpreter.allocate_tensors() # Get model details self.input_details = self.interpreter.get_input_details() self.output_details = self.interpreter.get_output_details() self.height = self.input_details[0]['shape'][1] self.width = self.input_details[0]['shape'][2] self.floating_model = (self.input_details[0]['dtype'] == np.float32) self.input_mean = 127.5 self.input_std = 127.5 def classify(self, image_dir): images = glob.glob(image_dir + '/*.jpg') classes_list = [] scores_list = [] boxes_list =[] for image_path in images: print('Classifying: {}'.format(image_path)) # Load image and resize to expected shape [1xHxWx3] image = cv2.imread(image_path) image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) imH, imW, _ = image.shape image_resized = cv2.resize(image_rgb, (self.width, self.height)) input_data = np.expand_dims(image_resized, axis=0) # Normalize pixel values if using a floating model (i.e. if model is non-quantized) if self.floating_model: input_data = (np.float32(input_data) - self.input_mean) / self.input_std # Perform the actual detection by running the model with the image as input self.interpreter.set_tensor(self.input_details[0]['index'],input_data) self.interpreter.invoke() boxes = self.interpreter.get_tensor(self.output_details[0]['index'])[0] # Bounding box coordinates of detected objects classes = self.interpreter.get_tensor(self.output_details[1]['index'])[0] # Class index of detected objects scores = self.interpreter.get_tensor(self.output_details[2]['index'])[0] # Confidence of detected objects boxes_list.append(boxes[scores > self.min_conf_threshold]) classes_list.append(classes[scores > self.min_conf_threshold]) scores_list.append(scores[scores > self.min_conf_threshold]) # Get bounding box coordinates and draw box # Interpreter can return coordinates that are outside of image dimensions, need to force them to be within image using max() and min() objects_dict ={} for i in range(len(scores)): if ((scores[i] > self.min_conf_threshold) and (scores[i] <= 1.0)): ymin = int(max(1,(boxes[i][0] * imH))) xmin = int(max(1,(boxes[i][1] * imW))) ymax = int(min(imH,(boxes[i][2] * imH))) xmax = int(min(imW,(boxes[i][3] * imW))) print((xmin,ymin), (xmax,ymax),(imH,imW)) cv2.rectangle(image, (xmin,ymin), (xmax,ymax), (10, 255, 0), 2) # Draw label object_name = self.labels[int(classes[i])] # Look up object name from "labels" array using class index objects_dict[object_name] = [(xmin,ymin), (xmax,ymax),(imH,imW)] label = '%s: %d%%' % (object_name, int(scores[i]*100)) # Example: 'person: 72%' labelSize, baseLine = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.7, 2) # Get font size label_ymin = max(ymin, labelSize[1] + 10) # Make sure not to draw label too close to top of window cv2.rectangle(image, (xmin, label_ymin-labelSize[1]-10), (xmin+labelSize[0], label_ymin+baseLine-10), (255, 255, 255), cv2.FILLED) # Draw white box to put label text in cv2.putText(image, label, (xmin, label_ymin-7), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 0), 2) # Draw label text classes_list.append(classes[scores > self.min_conf_threshold]) scores_list.append(scores[scores > self.min_conf_threshold]) objects_detected = {} for classes in classes_list: objects = set([self.labels[int(c)] for c in classes]) for obj in objects: if obj in objects_detected.keys(): objects_detected[obj] += 1 else: objects_detected[obj] = 1 return boxes_list, classes_list, scores_list, objects_detected, objects_dict if __name__ == '__main__': model = ObjectClassificationModel('Sample_TFLite_model', '/home/pi/Pictures/scav_hunt') classes, scores, objects = model.classify(os.path.join(model.image_dir, 'archive/orange'))

48.440678

192

0.607476

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17,148

4.627704

0.146802

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0.025457

0.023866

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0.070588

0

null

0

1

0

null

0

5

28e50161cd6d1fffd9c647d21db06debece1cf27

61

py

Python

qunetsim/__init__.py

pritamsinha2304/QuNetSim

65a7486d532816724b5c98cfdcc0910404bfe0e2

[ "MIT" ]

61

2020-02-15T00:59:20.000Z

2022-03-08T10:29:23.000Z

qunetsim/__init__.py

pritamsinha2304/QuNetSim

65a7486d532816724b5c98cfdcc0910404bfe0e2

[ "MIT" ]

50

2020-01-28T12:18:50.000Z

2021-12-16T21:38:19.000Z

qunetsim/__init__.py

pritamsinha2304/QuNetSim

65a7486d532816724b5c98cfdcc0910404bfe0e2

[ "MIT" ]

27

2020-01-21T12:59:28.000Z

2022-02-21T14:23:00.000Z

from .components import Host, Network from .objects import *

20.333333

37

0.786885

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0

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0

1

0

1

0

5

e9224fc9d93e1b11c5a9a3e8767f4d4a54b0d397

159

py

Python

persistent/errors.py

fictorial/python-object-persistence

93331e6e94ef356fe51ad377a67ed85225406943

[ "MIT" ]

1

2020-01-18T01:56:47.000Z

persistent/errors.py

fictorial/python-object-persistence

93331e6e94ef356fe51ad377a67ed85225406943

[ "MIT" ]

null

persistent/errors.py

fictorial/python-object-persistence

93331e6e94ef356fe51ad377a67ed85225406943

[ "MIT" ]

1

2021-03-28T05:23:17.000Z

class UniquenessError(ValueError): def __init__(self, index_name): ValueError.__init__(self, index_name) class NotFoundError(KeyError): pass

19.875

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1

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null

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1

0

5

3a88dc9b7a19489dfbe01bdc504291e06dfd9f10

1,626

py

Python

test/unittests/test_GroundWatLE.py

mudkipmaster/gwlf-e

9e058445537dd32d1916f76c4b73ca64261771cd

[ "Apache-2.0" ]

null

test/unittests/test_GroundWatLE.py

mudkipmaster/gwlf-e

9e058445537dd32d1916f76c4b73ca64261771cd

[ "Apache-2.0" ]

6

2018-07-24T22:46:28.000Z

2018-07-29T19:13:09.000Z

test/unittests/test_GroundWatLE.py

mudkipmaster/gwlf-e

9e058445537dd32d1916f76c4b73ca64261771cd

[ "Apache-2.0" ]

1

2018-07-24T18:22:01.000Z

import numpy as np from VariableUnittest import VariableUnitTest from gwlfe.Input.WaterBudget import GroundWatLE class TestGroundWatLE(VariableUnitTest): def test_GroundWatLE_ground_truth(self): z = self.z np.testing.assert_array_almost_equal( np.load(self.basepath + "/GroundWatLE.npy"), GroundWatLE.GroundWatLE(z.NYrs, z.DaysMonth, z.Temp, z.InitSnow_0, z.Prec, z.NRur, z.NUrb, z.Area, z.CNI_0, z.AntMoist_0, z.Grow_0, z.CNP_0, z.Imper, z.ISRR, z.ISRA, z.CN, z.UnsatStor_0, z.KV, z.PcntET, z.DayHrs, z.MaxWaterCap, z.SatStor_0, z.RecessionCoef, z.SeepCoef), decimal=7) def test_GroundWatLE(self): z = self.z np.testing.assert_array_almost_equal( GroundWatLE.GroundWatLE_f(z.NYrs, z.DaysMonth, z.Temp, z.InitSnow_0, z.Prec, z.NRur, z.NUrb, z.Area, z.CNI_0, z.AntMoist_0, z.Grow_0, z.CNP_0, z.Imper, z.ISRR, z.ISRA, z.CN, z.UnsatStor_0, z.KV, z.PcntET, z.DayHrs, z.MaxWaterCap, z.SatStor_0, z.RecessionCoef, z.SeepCoef), GroundWatLE.GroundWatLE(z.NYrs, z.DaysMonth, z.Temp, z.InitSnow_0, z.Prec, z.NRur, z.NUrb, z.Area, z.CNI_0, z.AntMoist_0, z.Grow_0, z.CNP_0, z.Imper, z.ISRR, z.ISRA, z.CN, z.UnsatStor_0, z.KV, z.PcntET, z.DayHrs, z.MaxWaterCap, z.SatStor_0, z.RecessionCoef, z.SeepCoef), decimal=7)

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3a89137dc5d68a37f1bbd913ab2462d253b89b3e

37

py

Python

reproducibility_project/src/engine_input/cassandra/__init__.py

chrisjonesBSU/reproducibility_study

34ab6542a28742d734db550293795992f33cf0a6

[ "MIT" ]

3

2021-08-12T16:42:01.000Z

2021-11-20T00:27:49.000Z

reproducibility_project/src/engine_input/cassandra/__init__.py

chrisjonesBSU/reproducibility_study

34ab6542a28742d734db550293795992f33cf0a6

[ "MIT" ]

67

2021-08-09T23:30:17.000Z

2022-03-24T16:38:59.000Z

reproducibility_project/src/engine_input/cassandra/__init__.py

chrisjonesBSU/reproducibility_study

34ab6542a28742d734db550293795992f33cf0a6

[ "MIT" ]

17

2021-08-09T23:38:40.000Z

2022-02-24T22:40:28.000Z

"""Cassandra engine input module."""

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0

1

0

5

3ab384e4234a4adcfb3c0cab22507c8d19600ca3

172

py

Python

chatpls/structures/__init__.py

jaobernardi/chatpls

eaf79b72466cdfbf8168b8e059859c707cfde8df

[ "MIT" ]

1

2021-05-08T22:38:18.000Z

chatpls/structures/__init__.py

jaobernardi/chatpls

eaf79b72466cdfbf8168b8e059859c707cfde8df

[ "MIT" ]

2

2021-05-06T09:19:06.000Z

2021-05-06T09:19:39.000Z

chatpls/structures/__init__.py

jaobernardi/chatpls

eaf79b72466cdfbf8168b8e059859c707cfde8df

[ "MIT" ]

null

from .http import Server, Response, Request from .wrappers import EventResponse, RelativeJsonFile, Config from .twitch import TwitchAPI from .database import User, Database

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1

0

1

0

1

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5

c93bd3a15adaeec5908e6e9444c3a3ef6c610155

1,171

py

Python

src/training/Core2/Chapter5Numbers/Exercise5_6.py

MagicForest/Python

8af56e9384061504f05b229467c922ba71a433cb

[ "Apache-2.0" ]

null

src/training/Core2/Chapter5Numbers/Exercise5_6.py

MagicForest/Python

8af56e9384061504f05b229467c922ba71a433cb

[ "Apache-2.0" ]

null

src/training/Core2/Chapter5Numbers/Exercise5_6.py

MagicForest/Python

8af56e9384061504f05b229467c922ba71a433cb

[ "Apache-2.0" ]

null

def parseExpression(expression): operators = ['**', '+', '-', '*', '/', '%'] operator = '+' for currOperator in operators: if expression.__contains__(currOperator): operator = currOperator break if bool(operator): operands = expression.split(operator) return {'firstOperand': int(operands[0]), 'operator': operator, 'secondOperand': int(operands[1])} def add(firstOperand, secondOperand): return firstOperand + secondOperand def subtract(firstOperand, secondOperand): return firstOperand - secondOperand def multiply(firstOperand, secondOperand): return firstOperand * secondOperand def divide(firstOperand, secondOperand): return firstOperand / secondOperand def mod(firstOperand, secondOperand): return firstOperand % secondOperand def pow(firstOperand, secondOperand): return firstOperand ** secondOperand def calculate(firstOperand, operator, secondOperand): operatorMappingFunc = {'+': add, '-': subtract, '*': multiply, '/': divide, '%': mod, '**': pow} return operatorMappingFunc[operator](firstOperand, secondOperand)

29.275

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0.415601

0.237852

0.329923

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0.207515

1,171

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0

null

1

0

null

0

1

0

1

0

5

a39098d812e8eb68ed52c197237e51ff40205d53

87

py

Python

tests/fixtures/abcd_package/test_c.py

venmo/nose-randomly

39db5db71a226ffdb6572d5785638e0a16379cfb

[ "BSD-3-Clause" ]

19

2015-07-30T17:27:56.000Z

2021-08-10T07:19:43.000Z

tests/fixtures/abcd_package/test_c.py

venmo/nose-randomly

39db5db71a226ffdb6572d5785638e0a16379cfb

[ "BSD-3-Clause" ]

11

2016-02-14T10:33:44.000Z

2016-10-28T12:38:35.000Z

tests/fixtures/abcd_package/test_c.py

adamchainz/nose-randomly

8a3fbeaf7cc5452c44da8c7e7573fe89391c8260

[ "BSD-3-Clause" ]

4

2016-06-01T06:04:46.000Z

2016-10-26T11:41:53.000Z

from unittest import TestCase class C(TestCase): def test_it(self): pass

12.428571

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0.666667

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0.916667

0

0.264368

87

6

30

14.5

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1

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false

0.25

0

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

6e8d32cda8a3901c6e46ce26252c14adf9645b09

329

py

Python

uvicore/http/routing/__init__.py

coboyoshi/uvicore

9cfdeeac83000b156fe48f068b4658edaf51c8de

[ "MIT" ]

null

uvicore/http/routing/__init__.py

coboyoshi/uvicore

9cfdeeac83000b156fe48f068b4658edaf51c8de

[ "MIT" ]

null

uvicore/http/routing/__init__.py

coboyoshi/uvicore

9cfdeeac83000b156fe48f068b4658edaf51c8de

[ "MIT" ]

null

# Public API used in packages routes and controllers from .api_router import ApiRoute, ApiRouter from .auto_api import AutoApi from .guard import Guard from .model_router import ModelRouter from .router import Router from .router import Routes from .router import Routes as Controller from .web_router import WebRoute, WebRouter

32.9

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0.829787

48

329

5.604167

0.479167

0.267658

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0.163569

0

0.136778

329

9

53

36.555556

0.947183

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1

0

true

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1

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null

1

0

1

0

1

0

null

0

1

0

1

0

5

6ebc43029760f14ec70645af215efb5d20bf6399

401

py

Python

backend/messaging/models.py

vrindger/cb-test

3b0122dfbd0b4ca905a82ec8d4279582eeb71d6f

[ "Apache-2.0" ]

null

backend/messaging/models.py

vrindger/cb-test

3b0122dfbd0b4ca905a82ec8d4279582eeb71d6f

[ "Apache-2.0" ]

null

backend/messaging/models.py

vrindger/cb-test

3b0122dfbd0b4ca905a82ec8d4279582eeb71d6f

[ "Apache-2.0" ]

null

from django.db import models class Message(models.Model): sender_email = models.CharField(max_length=40) recipient_email = models.CharField(max_length=40, default='') title = models.CharField(max_length=40) message_body = models.CharField(max_length=100) def _str_(self): return 'To: ' + self.recipient_email + 'Title: ' + self.title + 'MessageBody: ' + self.message_body

40.1

107

0.715711

52

401

5.307692

0.480769

0.217391

0.26087

0.347826

0.318841

0.224638

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0.026786

0.162095

401

10

107

40.1

0.794643

0

0.059701

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1

0.125

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0

0.125

1

0

null

1

0

null

0

1

0

5

6eca76199ad0d68006c4197b13af137e96972fe0

184

py

Python

com/bdu/chapter/four/Conditions.py

engineerpawan/python-examples

80806f8ab0fd7d96c2074989559ab4843d1e0be3

[ "MIT" ]

null

com/bdu/chapter/four/Conditions.py

engineerpawan/python-examples

80806f8ab0fd7d96c2074989559ab4843d1e0be3

[ "MIT" ]

null

com/bdu/chapter/four/Conditions.py

engineerpawan/python-examples

80806f8ab0fd7d96c2074989559ab4843d1e0be3

[ "MIT" ]

null

album_year = 1983 if album_year > 1980: print "Album year is greater than 1980" elif (album_year > 1990): print "greater than 1990" else: print "album is less than 1980"

20.444444

43

0.690217

29

184

4.275862

0.448276

0.290323

0

0.170213

0.233696

184

9

44

20.444444

0.70922

0

0.38587

0

null

0

null

0.428571

1

0

null

1

0

1

0

null

0

1

0

1

0

5

42c906967f55d6427bfe9295a4a4a109862f9d47

68

py

Python

WORC/facade/__init__.py

MStarmans91/WORC

b6b8fc2ccb7d443a69b5ca20b1d6efb65b3f0fc7

[ "ECL-2.0", "Apache-2.0" ]

47

2018-01-28T14:08:15.000Z

2022-03-24T16:10:07.000Z

WORC/facade/__init__.py

JZK00/WORC

14e8099835eccb35d49b52b97c0be64ecca3809c

[ "ECL-2.0", "Apache-2.0" ]

13

2018-08-28T13:32:57.000Z

2020-10-26T16:35:59.000Z

WORC/facade/__init__.py

JZK00/WORC

14e8099835eccb35d49b52b97c0be64ecca3809c

[ "ECL-2.0", "Apache-2.0" ]

16

2017-11-13T10:53:36.000Z

2022-03-18T17:02:04.000Z

from .simpleworc import SimpleWORC from .basicworc import BasicWORC

22.666667

34

0.852941

8

68

7.25

0.5

0

0.117647

68

2

35

34

0.966667

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

42e8ec7828edddcfd480403a89aee3bc13982023

122

py

Python

session03_test/test.py

heawon99/Repository-NEXT_HW_new

e73fac56469b7518034322f0d2fefe5f95c8c164

[ "MIT" ]

null

session03_test/test.py

heawon99/Repository-NEXT_HW_new

e73fac56469b7518034322f0d2fefe5f95c8c164

[ "MIT" ]

null

session03_test/test.py

heawon99/Repository-NEXT_HW_new

e73fac56469b7518034322f0d2fefe5f95c8c164

[ "MIT" ]

null

def add(a, b): return a + b add() def add(a, b): print(a+b) def say_hello(): print("hello") say_hello()

8.133333

18

0.532787

22

122

2.863636

0.363636

0.126984

0.222222

0.253968

0

0.278689

122

14

19

8.714286

0.715909

0

0.25

0

0.041667

0

1

0.375

false

0

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0.5

0.25

1

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null

0

1

0

null

0

1

0

1

0

5

42ff12fce56ed9c58bba61243f72c9f7bd18e33b

229

py

Python

src/airfly/_vendor/airflow/contrib/operators/bigquery_to_gcs.py

ryanchao2012/airfly

230ddd88885defc67485fa0c51f66c4a67ae98a9

[ "MIT" ]

7

2021-09-27T11:38:48.000Z

2022-02-01T06:06:24.000Z

src/airfly/_vendor/airflow/contrib/operators/bigquery_to_gcs.py

ryanchao2012/airfly

230ddd88885defc67485fa0c51f66c4a67ae98a9

[ "MIT" ]

null

src/airfly/_vendor/airflow/contrib/operators/bigquery_to_gcs.py

ryanchao2012/airfly

230ddd88885defc67485fa0c51f66c4a67ae98a9

[ "MIT" ]

null

# Auto generated by 'inv collect-airflow' from airfly._vendor.airflow.providers.google.cloud.transfers.bigquery_to_gcs import ( BigQueryToGCSOperator, ) class BigQueryToCloudStorageOperator(BigQueryToGCSOperator): pass

25.444444

85

0.816594

23

229

8

0.913043

0

0.10917

229

8

86

28.625

0.901961

0.170306

0

1

0

1

0

true

0.2

0

0.4

0

1

0

null

0

1

0

1

0

null

0

1

0

5

6e2eadf2c87144eeae292fb7c2109477c366633c

108

py

Python

q2_gcn_norm/__init__.py

Jiung-Wen/q2-gcn-norm

90a756c98a0fb5defd06afb2d7bbbd95de9df5c4

[ "BSD-3-Clause" ]

1

2022-03-02T18:03:04.000Z

q2_gcn_norm/__init__.py

Jiung-Wen/q2-gcn-norm

90a756c98a0fb5defd06afb2d7bbbd95de9df5c4

[ "BSD-3-Clause" ]

4

2019-12-07T08:27:51.000Z

2021-11-29T19:43:29.000Z

q2_gcn_norm/__init__.py

Jiung-Wen/q2-gcn-norm

90a756c98a0fb5defd06afb2d7bbbd95de9df5c4

[ "BSD-3-Clause" ]

null

from ._copy_num_normalize import copy_num_normalize __all__ = 'copy_num_normalize' __version__ = '2021.11'

21.6

51

0.824074

15

108

4.933333

0.6

0.283784

0.648649

0

0.061856

0.101852

108

4

52

27

0.701031

0

0.231481

0

1

0

false

0

0.333333

0

0.333333

0

1

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null

1

0

1

0

null

0

1

0

5

6e2ffb703f7d37de8531f31197b33cdcd1a9e1c2

17

py

Python

Compiler Design Lab/ChocoPy_LLVM_Compiler/custom_tests/IfExpr.py

Abhishek-Aditya-bs/Lab-Projects-and-Assignments

fd2681a1c7453367a4df1790e58afb312f13998c

[ "MIT" ]

null

Compiler Design Lab/ChocoPy_LLVM_Compiler/custom_tests/IfExpr.py

Abhishek-Aditya-bs/Lab-Projects-and-Assignments

fd2681a1c7453367a4df1790e58afb312f13998c

[ "MIT" ]

null

Compiler Design Lab/ChocoPy_LLVM_Compiler/custom_tests/IfExpr.py

Abhishek-Aditya-bs/Lab-Projects-and-Assignments

fd2681a1c7453367a4df1790e58afb312f13998c

[ "MIT" ]

null

5 if True else 10

17

0.764706

5

17

2.6

1

0

0.230769

0.235294

17

1

17

0.769231

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

5

284f0d6e28462adae12c1ed6e4bf40d44d4b762d

204

py

Python

cmp_command_acceptor/app/controllers/interfaces/CommandFactory.py

andrii-z4i/xmind-telegram

82e50ae0ada048b87a2c082bbdd4510e02cb3694

[ "MIT" ]

null

cmp_command_acceptor/app/controllers/interfaces/CommandFactory.py

andrii-z4i/xmind-telegram

82e50ae0ada048b87a2c082bbdd4510e02cb3694

[ "MIT" ]

16

2018-05-07T09:42:56.000Z

2018-11-19T06:05:51.000Z

cmp_command_acceptor/app/controllers/interfaces/CommandFactory.py

andrii-z4i/xmind-telegram

82e50ae0ada048b87a2c082bbdd4510e02cb3694

[ "MIT" ]

null

from abc import ABC, abstractmethod from shared.model.Command import Command class CommandFactory(ABC): @abstractmethod def prepare_command(self) -> Command: raise NotImplementedError()

22.666667

41

0.754902

22

204

6.954545

0.636364

0.222222

0

0.176471

204

8

42

25.5

0.910714

0

1

0.166667

false

0

0.333333

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

285dce87a285a443c4526d18957bbd35bf0d9bd1

212

py

Python

features/features_script.py

christophe-joyet/inphinity

a100fef2b6963c32c75f86e8d34c9a997dd4bba0

[ "MIT" ]

null

features/features_script.py

christophe-joyet/inphinity

a100fef2b6963c32c75f86e8d34c9a997dd4bba0

[ "MIT" ]

4

2019-03-05T09:34:02.000Z

2019-03-29T12:04:26.000Z

features/features_script.py

christophe-joyet/inphinity

a100fef2b6963c32c75f86e8d34c9a997dd4bba0

[ "MIT" ]

null

#!/usr/bin/python # -*- coding: utf-8 -*- import sys sys.path.insert(0, './') from features import features_functions features_functions.createFeaturesFile('Bacterium_id_5190.csv', './features/CSV_files', 5190)

26.5

92

0.745283

28

212

5.464286

0.714286

0.222222

0

0.051546

0.084906

212

8

92

26.5

0.737113

0.179245

0

0.248555

0.121387

0

1

0

true

0

0.5

0

0.5

0

1

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null

1

0

1

0

null

0

1

0

1

0

5

287fb9c5c9e90bb4c1fedf17ce8a0a513bde5d55

141

py

Python

observatoire-de-paris/Granotek/Appli Python/webcam_analyzer/main.py

S0nzero/iCreate2019

4126c1da4fcf226d43a064e1cd0081491dfc71a5

[ "MIT" ]

null

observatoire-de-paris/Granotek/Appli Python/webcam_analyzer/main.py

S0nzero/iCreate2019

4126c1da4fcf226d43a064e1cd0081491dfc71a5

[ "MIT" ]

null

observatoire-de-paris/Granotek/Appli Python/webcam_analyzer/main.py

S0nzero/iCreate2019

4126c1da4fcf226d43a064e1cd0081491dfc71a5

[ "MIT" ]

null

import tkinter from app import App # Create a window and pass it to the Application object App(tkinter.Tk(), "Decouvre ta planete", 0)

23.5

56

0.730496

23

141

4.478261

0.826087

0

0.00885

0.198582

141

6

57

23.5

0.902655

0.375887

0

0.231707

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

953599920cfa6c0881ce87344a1251d84c55c6b1

312

py

Python

python_programs/functions/printAsterix.py

Lioncat2002/CSE-programs

48c60a34343acd435f2c5a3e731d3f71bb54158c

[ "MIT" ]

1

2021-11-15T15:21:29.000Z

python_programs/functions/printAsterix.py

Lioncat2002/CSE-programs

48c60a34343acd435f2c5a3e731d3f71bb54158c

[ "MIT" ]

null

python_programs/functions/printAsterix.py

Lioncat2002/CSE-programs

48c60a34343acd435f2c5a3e731d3f71bb54158c

[ "MIT" ]

2

2021-11-14T01:45:51.000Z

2021-11-15T15:21:08.000Z

''' Write a Python function named printAsterisks that is passed a positive integer value n, and prints out a line of n asterisks. If n is greater than 75, then only 75 asterisks should be displayed. ''' def printAsterix(n): return '*'*(n if n<75 else 75) print(printAsterix(int(input("Enter number: "))))

31.2

99

0.724359

51

312

4.431373

0.72549

0.026549

0

0.031128

0.176282

312

9

100

34.666667

0.848249

0.625

0

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0

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false

0

0.333333

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null

0

1

0

null

0

1

0

1

0

5

957bf59b10b1661f5290871d5678d8405f25fbed

1,419

py

Python

swing_server/helpers.py

docker-swing/swing-server

48ee777f1464b45cfb9d316f728b4b84a64ecd3d

[ "Apache-2.0" ]

1

2021-06-06T11:56:49.000Z

swing_server/helpers.py

docker-swing/swing-server

48ee777f1464b45cfb9d316f728b4b84a64ecd3d

[ "Apache-2.0" ]

null

swing_server/helpers.py

docker-swing/swing-server

48ee777f1464b45cfb9d316f728b4b84a64ecd3d

[ "Apache-2.0" ]

null

import os import re from werkzeug.security import check_password_hash, generate_password_hash version_regex = r'^\d+(?:\.\d+)+$' name_regex = r'^[a-z]+(?:-[a-z]+)*$' zip_regex = r'^[a-z]+(?:-[a-z]+)*\-\d+(?:\.\d+)+\.zip' def is_valid_filename(filename) -> bool: return bool(re.match(zip_regex, filename)) def is_valid_version(version) -> bool: return bool(re.match(version_regex, version)) def is_valid_chart_name(name) -> bool: return bool(re.match(name_regex, name)) def is_readable_dir(path: str) -> bool: return os.path.isdir(path) and os.access(path, os.R_OK) def to_dicts(arr): return [x.to_dict() for x in arr] def create_directory(path: str): if not os.path.exists(path): os.makedirs(path) def hash_password(password: str) -> str: """ Create a hash of the password using randomly generated salt. """ return generate_password_hash(password, salt_length=12) def check_password(password: str, hashed_password: str) -> bool: """ Compare the password against its hashed variant. """ return check_password_hash(hashed_password, password) def parse_archive_filename(filename): """ Read the filename of the requested archive and return both the chart name and the release version. """ chunks = filename[:-4].split('-') chart_name = '-'.join(chunks[:-1]) version = chunks[-1] return chart_name, version

23.65

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4.466019

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0.178295

1,419

59

74

24.050847

0.784734

0.146582

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0.033592

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1

0.321429

false

0.178571

0.107143

0.178571

0.714286

0

null

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1

0

null

0

1

0

1

0

1

0

5

95c9b2d794a55186aa36dbdd1eacfa83515abb49

6,818

py

Python

tests/test_audio.py

mlxyz/insynth

0d2ad6d6177944978e6d85990b9991a614d75b68

[ "MIT" ]

null

tests/test_audio.py

mlxyz/insynth

0d2ad6d6177944978e6d85990b9991a614d75b68

[ "MIT" ]

1

2021-12-06T20:46:20.000Z

2021-12-06T20:48:37.000Z

tests/test_audio.py

mlxyz/insynth

0d2ad6d6177944978e6d85990b9991a614d75b68

[ "MIT" ]

1

2021-12-06T20:45:50.000Z

import unittest import numpy as np from insynth.perturbators.audio import AudioBackgroundWhiteNoisePerturbator, AudioPitchPerturbator, \ AudioClippingPerturbator, AudioVolumePerturbator, AudioEchoPerturbator, AudioShortNoisePerturbator, \ AudioImpulseResponsePerturbator, AudioBackgroundNoisePerturbator class TestAudio(unittest.TestCase): def _generate_random_audio(self): data = np.random.uniform(-1, 1, 44100) return data def test_AudioBackgroundWhiteNoisePerturbator_with_noise(self): input_signal = self._generate_random_audio() perturbator = AudioBackgroundWhiteNoisePerturbator(p=1.0, noise_prob=type('', (object,), {'rvs': lambda _: 1.0})(), noise_prob_args={}) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) # assert arrays are not equal np.testing.assert_raises(AssertionError, np.testing.assert_array_equal, input_signal, output_signal) def test_AudioBackgroundWhiteNoisePerturbator_without_noise(self): input_signal = self._generate_random_audio() perturbator = AudioBackgroundWhiteNoisePerturbator(p=1.0, noise_prob=type('', (object,), {'rvs': lambda _: 0.0})(), noise_prob_args={}) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_array_equal(input_signal, output_signal) def test_AudioPitchPerturbator_with_pitch_change(self): input_signal = self._generate_random_audio() perturbator = AudioPitchPerturbator(p=1.0, pitch_prob=type('', (object,), {'rvs': lambda _: 12})(), pitch_prob_args={}) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_raises(AssertionError, np.testing.assert_array_equal, input_signal, output_signal) def test_AudioPitchPerturbator_without_pitch_change(self): input_signal = self._generate_random_audio() perturbator = AudioPitchPerturbator(p=1.0, pitch_prob=type('', (object,), {'rvs': lambda _: 0})(), pitch_prob_args={}) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_array_almost_equal(input_signal, output_signal, 1) def test_AudioClippingPerturbator_with_clipping(self): input_signal = self._generate_random_audio() perturbator = AudioClippingPerturbator(p=1.0, clipping_prob=type('', (object,), {'rvs': lambda _: 50})(), clipping_prob_args={}) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_raises(AssertionError, np.testing.assert_array_equal, input_signal, output_signal) def test_AudioClippingPerturbator_without_clipping(self): input_signal = self._generate_random_audio() perturbator = AudioClippingPerturbator(p=1.0, clipping_prob=type('', (object,), {'rvs': lambda _: 0})(), clipping_prob_args={}) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_array_almost_equal(input_signal, output_signal, 1) def test_AudioVolumePerturbator_with_volume_change(self): input_signal = self._generate_random_audio() perturbator = AudioVolumePerturbator(p=1.0, volume_prob=type('', (object,), {'rvs': lambda _: 10})(), volume_prob_args={}) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_raises(AssertionError, np.testing.assert_array_equal, input_signal, output_signal) def test_AudioVolumePerturbator_without_volume_change(self): input_signal = self._generate_random_audio() perturbator = AudioVolumePerturbator(p=1.0, volume_prob=type('', (object,), {'rvs': lambda _: 0})(), volume_prob_args={}) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_array_almost_equal(input_signal, output_signal, 4) def test_AudioEchoPerturbator_with_echo(self): input_signal = self._generate_random_audio() perturbator = AudioEchoPerturbator(p=1.0, echo_prob=type('', (object,), {'rvs': lambda _: 1.0})(), echo_prob_args={}) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_raises(AssertionError, np.testing.assert_array_equal, input_signal, output_signal) def test_AudioEchoPerturbator_without_echo(self): input_signal = self._generate_random_audio() perturbator = AudioEchoPerturbator(p=1.0, echo_prob=type('', (object,), {'rvs': lambda _: 0.0})(), echo_prob_args={}) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_array_equal(output_signal, input_signal * 2) def test_AudioBackgroundNoisePerturbator_with_noise(self): input_signal = self._generate_random_audio() perturbator = AudioBackgroundNoisePerturbator(p=1.0, noise_types=['']) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_raises(AssertionError, np.testing.assert_array_equal, input_signal, output_signal) def test_AudioShortNoisePerturbator_with_noise(self): input_signal = self._generate_random_audio() perturbator = AudioShortNoisePerturbator(p=1.0, noise_types=['']) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_raises(AssertionError, np.testing.assert_array_equal, input_signal, output_signal) def test_AudioImpulseResponsePerturbator_with_noise(self): input_signal = self._generate_random_audio() perturbator = AudioImpulseResponsePerturbator(p=1.0, impulse_types=['']) output_signal,sample_rate = perturbator.apply((input_signal, 44100)) np.testing.assert_raises(AssertionError, np.testing.assert_array_equal, input_signal, output_signal) if __name__ == '__main__': unittest.main()

51.263158

116

0.63919

663

6,818

6.19457

0.110106

0.104456

0.076698

0.060141

0.779888

0.779158

0.778184

0

0.023771

0.265767

6,818

132

117

51.651515

0.796644

0.00396

0

0.583333

0

0.005597

0

0.135417

1

0.145833

false

0

0.03125

0

0.197917

0

null

0

1

0

null

0

5

95ddc37bb84b1010a5d27edc321a76e524c3e67d

250

py

Python

apps/publications/translation.py

remocrevo/celus

682b13168eb475d7f970502113e756e40a899877

[ "MIT" ]

7

2020-02-20T13:24:40.000Z

2022-01-28T19:36:04.000Z

apps/publications/translation.py

techlib/czechelib-stats

ca132e326af0924740a525710474870b1fb5fd37

[ "MIT" ]

15

2020-04-28T13:09:02.000Z

2021-11-03T15:21:24.000Z

apps/publications/translation.py

techlib/czechelib-stats

ca132e326af0924740a525710474870b1fb5fd37

[ "MIT" ]

4

2020-02-20T13:48:30.000Z

2021-03-19T00:33:34.000Z

from modeltranslation.translator import translator, TranslationOptions from .models import Platform class PlatformTranslationOptions(TranslationOptions): fields = ('name', 'provider') translator.register(Platform, PlatformTranslationOptions)

25

70

0.828

20

250

10.35

0.65

0

0.1

250

9

71

27.777778

0.92

0

0.048

0

1

0

false

0

0.4

0

0.8

0

1

0

1

null

0

1

0

null

0

1

0

1

0

5

250677022d1e228c75eb5d1c4ef6c49f59a1155f

322

py

Python

alphatrade/__init__.py

algo2win/alpha_trade

85dc53e8f3a7fcc6a80f84a1e57a9fdf48022c72

[ "MIT" ]

21

2020-10-24T11:37:03.000Z

2022-03-22T07:24:15.000Z

alphatrade/__init__.py

algo2win/alpha_trade

85dc53e8f3a7fcc6a80f84a1e57a9fdf48022c72

[ "MIT" ]

27

2020-10-24T18:41:34.000Z

2022-03-24T06:09:44.000Z

alphatrade/__init__.py

algo2win/alpha_trade

85dc53e8f3a7fcc6a80f84a1e57a9fdf48022c72

[ "MIT" ]

14

2020-10-24T22:19:25.000Z

2022-03-13T14:46:53.000Z

from __future__ import unicode_literals, absolute_import from .alphatrade import AlphaTrade, TransactionType, OrderType, ProductType, LiveFeedType, Instrument from alphatrade import exceptions __all__ = ['AlphaTrade', 'TransactionType', 'OrderType', 'ProductType', 'LiveFeedType', 'Instrument', 'exceptions']

40.25

101

0.782609

28

322

8.642857

0.5

0.115702

0.165289

0.371901

0.553719

0

0.124224

322

7

102

46

0.858156

0

0.23913

0

1

0

false

0

0.6

0

0.6

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

256938a208ce388b46e2c3b15efa03a6b341bbcd

127

py

Python

cal/admin.py

yangd01234/up-two-date

8a2e044b2fd4fb53ea7fceef65955035b320e426

[ "MIT" ]

null

cal/admin.py

yangd01234/up-two-date

8a2e044b2fd4fb53ea7fceef65955035b320e426

[ "MIT" ]

10

2019-12-04T23:25:35.000Z

2022-02-10T09:19:45.000Z

cal/admin.py

yangd01234/up-two-date

8a2e044b2fd4fb53ea7fceef65955035b320e426

[ "MIT" ]

null

from django.contrib import admin from .models import Time # register models to show up on admin page admin.site.register(Time)

25.4

42

0.80315

21

127

4.857143

0.666667

0

0.141732

127

5

43

25.4

0.93578

0.314961

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

c2b6888637a7a14175544804420974aebc286e43

571

py

Python

qcnpy/costfunction.py

KristianWold/qcnpy

a77d588ec2c0b28c8f02ec24602d07013bedd9d4

[ "MIT" ]

null

qcnpy/costfunction.py

KristianWold/qcnpy

a77d588ec2c0b28c8f02ec24602d07013bedd9d4

[ "MIT" ]

null

qcnpy/costfunction.py

KristianWold/qcnpy

a77d588ec2c0b28c8f02ec24602d07013bedd9d4

[ "MIT" ]

null

import numpy as np class MSE: def __call__(self, y_pred, y): return 0.5 * np.mean((y_pred - y)**2) def derivative(self, y_pred, y): return y_pred - y class CrossEntropy: def __call__(self, y_pred, y): return -np.sum(y * np.log(y_pred)) def derivative(self, y_pred, y): return (y_pred - y) / (y_pred * (1 - y_pred)) class NoCost: def __call__(self, y_pred, y): return y_pred def derivative(self, y_pred, y): n_samples, n_targets = y_pred.shape return np.ones((n_samples, n_targets))

21.148148

53

0.602452

93

571

3.376344

0.290323

0.22293

0.171975

0.191083

0.547771

0.328025

0.22293

0

0.009639

0.273205

571

26

54

21.961538

0.746988

0

0.352941

0

1

0.352941

false

0

0.058824

0.294118

0.941176

0

null

1

0

1

0

null

0

1

0

1

0

5

c2cfa8ec3c9192d557cd889ec1226d91cd6ce827

2,054

py

Python

ciclo1_python/ucaldas/MisionTIC_UCaldas_Ciclo1/Andres Felipe Escallon Portilla/Semana2/Talleres/info_add_talleres/Tallersemana203/main.py

felipeescallon/mision_tic_2022

20496fc40b18d2e98114d6362928f34fde41aaae

[ "CC0-1.0" ]

7

2021-07-05T21:25:50.000Z

2021-11-09T11:09:41.000Z

ciclo1_python/ucaldas/MisionTIC_UCaldas_Ciclo1/Andres Felipe Escallon Portilla/Semana2/Talleres/info_add_talleres/Tallersemana203/main.py

felipeescallon/mision_tic_2022

20496fc40b18d2e98114d6362928f34fde41aaae

[ "CC0-1.0" ]

null

ciclo1_python/ucaldas/MisionTIC_UCaldas_Ciclo1/Andres Felipe Escallon Portilla/Semana2/Talleres/info_add_talleres/Tallersemana203/main.py

felipeescallon/mision_tic_2022

20496fc40b18d2e98114d6362928f34fde41aaae

[ "CC0-1.0" ]

null

""" Taller 2.3 Distancia mas corta # Tu nombre aquí Mayo xx-XX """ # Definición de Funciones (Dividir) #====================================================================== # E S P A C I O D E T R A B A J O A L U M N O # ===================================================================== def calcular_distancia_c1_a1(xc1,yc1,xa1,ya1): #TODO: comentarios #TODO: instrucciones return #------------------------------------------- def calcular_distancia_a1_ch(xa1,ya1,xch,ych): #TODO: comentarios #TODO: instrucciones return #------------------------------------------- def calcular_distancia_ch_a2(xch,ych,xa2,ya2): #TODO: comentarios #TODO: instrucciones return #------------------------------------------- def calcular_distancia_a2_c2(xa2,ya2,xc2,yc2): #TODO: comentarios #TODO: instrucciones return #------------------------------------------- def obtener_distancia_total (d1,d2,d3,d4): #TODO: comentarios #TODO: instrucciones return #====================================================================== # E S P A C I O P R E _ _ C O N F I G U R A D O # ===================================================================== #====================================================================== # Algoritmo principal Punto de entrada a la aplicación (Conquistar) # ===================================================================== #lectura coordenadas celular 1 #TODO: instrucciones #lectura coordenadas antena 1 #TODO: instrucciones #lectura coordenadas central holi #TODO: instrucciones #lectura coordenadas antena 2 #TODO: instrucciones #lectura coordenadas celular 1 #TODO: una vez haga os puntos anteriores quite el simbolo de comentarios # y organice la identación #d1=calcular_distancia_c1_a1(xc1,yc1,xa1,ya1) #d2=calcular_distancia_a1_ch(xa1,ya1,xch,ych) #d3=calcular_distancia_ch_a2(xch,ych,xa2,ya2) #d4=calcular_distancia_a2_c2(xa2,ya2,xc2,yc2) #distancia_total=obtener_distancia_total (d1,d2,d3,d4) #print("La distancia otal es",distancia_total)

30.656716

72

0.519474

233

2,054

4.44206

0.381974

0.147826

0.091787

0.154589

0.687923

0.483092

0.443478

0.373913

0

0.030168

0.12853

2,054

66

73

31.121212

0.548045

0.802337

0

0.5

0

0.015152

0

1

0.5

false

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

c2d93bc1c24f5d226f84ab5033cafc2f5534b822

198

py

Python

app/constants/ignore.py

heart-your-health/valve

802fcd890da6fcdb2e8ff88b3be0f0b8277bec5c

[ "MIT" ]

null

app/constants/ignore.py

heart-your-health/valve

802fcd890da6fcdb2e8ff88b3be0f0b8277bec5c

[ "MIT" ]

2

2018-05-21T21:27:11.000Z

2020-03-12T19:32:57.000Z

app/constants/ignore.py

sageleaf/me

802fcd890da6fcdb2e8ff88b3be0f0b8277bec5c

[ "MIT" ]

1

2018-04-30T19:04:26.000Z

ignore_validation = { "/api/v1/profile": ("POST", "PUT"), "/api/v1/exchange": "GET", "/api/v1/validation": "GET", "/api/v1/meals/search" : "GET", "/api/v1/meals/browse" : "GET" }

28.285714

39

0.545455

25

198

4.28

0.48

0.233645

0.224299

0.242991

0

0.030864

0.181818

198

7

40

28.285714

0.62963

0

0.542714

0

1

0

false

0

1

0

null

1

0

1

0

null

0

5

6c2fe969de5ffd3d06d8f78819c59e7da7ccfa78

156

py

Python

UnitTests/UnitTestMissionPlanner/bin/Debug/Scripts/rc.py

EduardoAzoia/Integrador

88ba0371685f9aa0efe00dbc06f10881445197b3

[ "Apache-2.0" ]

null

UnitTests/UnitTestMissionPlanner/bin/Debug/Scripts/rc.py

EduardoAzoia/Integrador

88ba0371685f9aa0efe00dbc06f10881445197b3

[ "Apache-2.0" ]

null

UnitTests/UnitTestMissionPlanner/bin/Debug/Scripts/rc.py

EduardoAzoia/Integrador

88ba0371685f9aa0efe00dbc06f10881445197b3

[ "Apache-2.0" ]

null

print 'Start Script' for chan in range(1,9): Script.SendRC(chan,1500,False) Script.SendRC(3,1500,True) Script.Sleep(1000) Script.SendRC(3,1100,True)

17.333333

34

0.730769

28

156

4.107143

0.642857

0.313043

0.226087

0

0.143885

0.108974

156

9

35

17.333333

0.676259

0

0.077922

0

null

0

null

0.166667

1

0

null

1

0

1

0

null

0

1

0

5

6c4cc5fd9dbd2922188443efa2531eb19767642b

106

py

Python

goods/cleaning.py

DroppinDangles/inventory-tracker

ae1f15eecafb240f1d6535d6f3e37d9356bf20e9

[ "MIT" ]

null

goods/cleaning.py

DroppinDangles/inventory-tracker

ae1f15eecafb240f1d6535d6f3e37d9356bf20e9

[ "MIT" ]

null

goods/cleaning.py

DroppinDangles/inventory-tracker

ae1f15eecafb240f1d6535d6f3e37d9356bf20e9

[ "MIT" ]

null

#import goods packages from goods.good import Good class Cleaning(Good): def __init__(self): pass

17.666667

28

0.735849

15

106

4.933333

0.733333

0

0.188679

106

6

29

17.666667

0.860465

0.198113

0

1

0.25

false

0.25

0

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

6c510b058b55ba13950201ac6c6f7a4545f2a249

73

py

Python

Discord_Together/__init__.py

Chrovo/Discord-Together.py

b1a947a17655009a6cc009b883db50e299c742c4

[ "MIT" ]

8

2021-06-28T14:01:43.000Z

2022-03-26T20:56:09.000Z

Discord_Together/__init__.py

Chrovo/Discord-Together.py

b1a947a17655009a6cc009b883db50e299c742c4

[ "MIT" ]

2

2021-06-18T19:40:32.000Z

2021-06-18T19:42:10.000Z

Discord_Together/__init__.py

Chrovo/Discord-Together.py

b1a947a17655009a6cc009b883db50e299c742c4

[ "MIT" ]

2

2021-06-16T20:05:29.000Z

2021-06-18T19:28:13.000Z

from .discordtogether import DiscordTogether from .exceptions import *

24.333333

45

0.821918

7

73

8.571429

0.571429

0

0.136986

73

2

46

36.5

0.952381

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

6c5a6c10f21aad21a0a1e2a9d78d12b54ab0ac57

187

py

Python

cnns/nnlib/attacks/empty.py

anonymous-user-commits/perturb-net

66fc7c4a1234fa34b92bcc85751f0a6e23d80a23

[ "MIT" ]

1

2018-03-25T13:19:46.000Z

cnns/nnlib/attacks/empty.py

anonymous-user-commits/perturb-net

66fc7c4a1234fa34b92bcc85751f0a6e23d80a23

[ "MIT" ]

null

cnns/nnlib/attacks/empty.py

anonymous-user-commits/perturb-net

66fc7c4a1234fa34b92bcc85751f0a6e23d80a23

[ "MIT" ]

null

import foolbox # Attack the image. class EmptyAttack(foolbox.attacks.Attack): def __call__(self, input_or_adv, label=None, unpack=True, **kwargs): return input_or_adv.copy()

26.714286

72

0.73262

26

187

4.961538

0.807692

0.108527

0.155039

0

0.15508

187

7

73

26.714286

0.816456

0.090909

0

1

0.25

false

0

0.25

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

667ad4f807388231aefaca9c917dc46673f00bcf

77

py

Python

tgmsg/__init__.py

KolosDan/tgmsg

1e735afe999f88e09fe9801e9c36ba763125dca5

[ "MIT" ]

null

tgmsg/__init__.py

KolosDan/tgmsg

1e735afe999f88e09fe9801e9c36ba763125dca5

[ "MIT" ]

null

tgmsg/__init__.py

KolosDan/tgmsg

1e735afe999f88e09fe9801e9c36ba763125dca5

[ "MIT" ]

1

2022-01-25T12:57:26.000Z

from .tg_client import TelegramClient from .models import keyboards, messages

38.5

39

0.857143

10

77

6.5

0.8

0

0.103896

77

2

39

38.5

0.942029

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

66915643aad9374fc2ace7ca20a618487db923d2

135

py

Python

lattedb/correlator/admin.py

callat-qcd/lattedb

75c06748f3d59332a84ec1b5794c215c5974a46f

[ "BSD-3-Clause" ]

1

2019-12-11T02:33:23.000Z

lattedb/correlator/admin.py

callat-qcd/lattedb

75c06748f3d59332a84ec1b5794c215c5974a46f

[ "BSD-3-Clause" ]

10

2020-01-29T17:06:01.000Z

2021-05-31T14:41:19.000Z

lattedb/correlator/admin.py

callat-qcd/lattedb

75c06748f3d59332a84ec1b5794c215c5974a46f

[ "BSD-3-Clause" ]

null

"""Admin view for correlation functions """ from espressodb.base.admin import register_admins register_admins("lattedb.correlator")

16.875

49

0.8

16

135

6.625

0.8125

0.264151

0

0.103704

135

7

50

19.285714

0.876033

0.266667

0

0.2

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

66c9e40227d7c9a8ab2a69b3493ee6bf8df86111

133

py

Python

config.py

oldcryptogeek/coinjerk-btcp

76d16b6c890bf1caa155ff07bca162526db08fc7

[ "MIT" ]

8

2020-09-22T03:40:31.000Z

2021-04-17T15:17:03.000Z

config.py

Zaxounette/coinjerk-btcp

76d16b6c890bf1caa155ff07bca162526db08fc7

[ "MIT" ]

5

2021-01-10T23:36:12.000Z

2022-02-19T06:46:18.000Z

config.py

Zaxounette/coinjerk-btcp

76d16b6c890bf1caa155ff07bca162526db08fc7

[ "MIT" ]

2

2021-01-03T23:36:39.000Z

2021-02-13T15:45:09.000Z

import os class Config(object): ENABLE_USER_REGISTRATION = \ (os.getenv("ENABLE_USER_REGISTRATION").lower() == "true")

19

65

0.676692

15

133

5.733333

0.733333

0.232558

0.511628

0

0.180451

133

6

66

22.166667

0.788991

0

0.210526

0.180451

0

1

0

false

0

0.25

0

0.75

0

1

0

null

1

0

1

0

null

0

1

0

5

66e7ec9a040eb2110e33b1cd4b9d3d9c80b71844

36

py

Python

target_athena/tests/__init__.py

beubeu13220/target-athena

ebe012bb6694f3685e4efa616a0acbd75c982fc5

[ "Apache-2.0" ]

4

2021-09-08T17:41:57.000Z

2021-12-22T03:30:06.000Z

target_athena/tests/__init__.py

beubeu13220/target-athena

ebe012bb6694f3685e4efa616a0acbd75c982fc5

[ "Apache-2.0" ]

19

2021-05-28T21:48:41.000Z

2021-08-23T04:17:01.000Z

target_athena/tests/__init__.py

beubeu13220/target-athena

ebe012bb6694f3685e4efa616a0acbd75c982fc5

[ "Apache-2.0" ]

7

2021-12-02T19:27:57.000Z

2022-03-09T08:23:12.000Z

"""Test suite for target-athena."""

18

35

0.666667

5

36

4.8

1

0

0.111111

36

1

36

0.75

0.805556

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

dd2d74d24d8f464c3d10a371dd62322793a10018

46

py

Python

cobra/main.py

Matheusblz/learning_things

69c16d30db8a79dffd5b83e91070aec7ab376b8a

[ "MIT" ]

null

cobra/main.py

Matheusblz/learning_things

69c16d30db8a79dffd5b83e91070aec7ab376b8a

[ "MIT" ]

null

cobra/main.py

Matheusblz/learning_things

69c16d30db8a79dffd5b83e91070aec7ab376b8a

[ "MIT" ]

null

print('Olá, mundo!') print('A cobra fumou!!')

15.333333

24

0.630435

7

46

4.142857

0.857143

0

0.108696

46

2

25

23

0.707317

0

0.565217

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

dd3f43f53c6543147a958041e4bdd51a4efe7ce0

123

py

Python

alexandria/__init__.py

HarkonenBade/alexandria

2e16dbf2d11c7928d0a661b28bfc2552b68cb3fe

[ "MIT" ]

null

alexandria/__init__.py

HarkonenBade/alexandria

2e16dbf2d11c7928d0a661b28bfc2552b68cb3fe

[ "MIT" ]

null

alexandria/__init__.py

HarkonenBade/alexandria

2e16dbf2d11c7928d0a661b28bfc2552b68cb3fe

[ "MIT" ]

null

from __future__ import absolute_import from flask import Flask app = Flask(__name__) from . import db from . import api

13.666667

38

0.780488

18

123

4.833333

0.5

0.229885

0

0.178862

123

8

39

15.375

0.861386

0

1

0

false

0

0.8

0

0.8

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

dd557a81fe3c9e869c8ff50c94a373fc86815309

99

py

Python

src/__init__.py

Kobie-Kirven/SCiMS

7e683b241f375277a38ee482e46b8dcc3a7cf186

[ "MIT" ]

null

src/__init__.py

Kobie-Kirven/SCiMS

7e683b241f375277a38ee482e46b8dcc3a7cf186

[ "MIT" ]

null

src/__init__.py

Kobie-Kirven/SCiMS

7e683b241f375277a38ee482e46b8dcc3a7cf186

[ "MIT" ]

null

# Author: Kobie Kirven # Davenport Lab - Penn State University # Date: 9-2-2021 from src import *

16.5

39

0.717172

15

99

4.733333

1

0

0.075

0.191919

99

5

40

19.8

0.8125

0.737374

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

dd8846de012d3b7b86af081fcef6f01877c3a6ca

187

py

Python

src/impacts_tools/p3.py

torimcd/impacts_tools

c5b78721e3f69077586e0778f6c961747a9d1bd4

[ "BSD-3-Clause" ]

1

2021-09-28T23:14:04.000Z

src/impacts_tools/p3.py

torimcd/impacts_tools

c5b78721e3f69077586e0778f6c961747a9d1bd4

[ "BSD-3-Clause" ]

3

2021-09-28T22:50:32.000Z

2022-01-13T22:28:18.000Z

src/impacts_tools/p3.py

torimcd/impacts_tools

c5b78721e3f69077586e0778f6c961747a9d1bd4

[ "BSD-3-Clause" ]

null

""" Classes for IMPACTS P3 Instruments """ class P3(object): """ """ def __init__(self, filepath, date): pass def readfile(self, filepath, ): pass

12.466667

39

0.540107

19

187

5.105263

0.736842

0.247423

0

0.015873

0.326203

187

15

40

12.466667

0.753968

0.181818

0

0.4

0

1

0.4

false

0.4

0

0.6

0

1

0

null

1

0

null

0

1

0

1

0

1

0

5

dd9305be7ca67706c1fd46c1c8375a70d2de7d3d

94

py

Python

parts/edag_transistor.py

baryluk/edag

675107e2078bcecb30768a5e96c7431104352024

[ "BSL-1.0" ]

null

parts/edag_transistor.py

baryluk/edag

675107e2078bcecb30768a5e96c7431104352024

[ "BSL-1.0" ]

null

parts/edag_transistor.py

baryluk/edag

675107e2078bcecb30768a5e96c7431104352024

[ "BSL-1.0" ]

null

#!/usr/bin/env python3 # Transistors. "2N3904" "2SC1815" # NPN? "2SA9012" "2SA1015" # PNP?

11.75

22

0.638298

11

94

5.454545

1

0

0.265823

0.159574

94

7

23

13.428571

0.493671

0.542553

0

0.586957

0

1

0

true

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

5

06d40e812ad2b3f573602b965f409bc16890ec0c

147

py

Python

backend/application/models/authbase/__init__.py

zxjlm/Christin

37d7a2d2a7e388a86625128729c31322da01c3cf

[ "MIT" ]

3

2021-07-07T23:32:22.000Z

2021-07-28T06:41:15.000Z

backend/application/models/authbase/__init__.py

zxjlm/Christin

37d7a2d2a7e388a86625128729c31322da01c3cf

[ "MIT" ]

1

2021-06-06T03:24:44.000Z

backend/application/models/authbase/__init__.py

zxjlm/Christin

37d7a2d2a7e388a86625128729c31322da01c3cf

[ "MIT" ]

2

2021-06-06T00:50:58.000Z

2021-06-06T05:04:16.000Z

from .resource import Resource from .resource_type import ResourceType from .role import Role from .user import User from .logs import AnalysesLog

24.5

39

0.829932

21

147

5.761905

0.428571

0.198347

0

0.136054

147

5

40

29.4

0.952756

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

6637a71c694404bcab4340b6cde23522fe6b6aad

75

py

Python

neko/trainers/__init__.py

SangheonOhWDC/neko

041a35d883ff7f7ad10ab8841c12a739fc2a73bc

[ "MIT" ]

11

2021-05-05T07:03:57.000Z

2021-12-10T04:48:55.000Z

neko/trainers/__init__.py

byin-cwi/neko

9a09cc5585f6a5f1cb25fefc88cc3ab461b8cb12

[ "MIT" ]

1

2021-08-02T19:02:30.000Z

2021-08-10T23:13:05.000Z

neko/trainers/__init__.py

byin-cwi/neko

9a09cc5585f6a5f1cb25fefc88cc3ab461b8cb12

[ "MIT" ]

2

2021-06-25T02:37:18.000Z

2022-02-18T09:29:20.000Z

from .base import Trainer from .gradcomp import GradientsComparisonTrainer

25

48

0.866667

8

75

8.125

0.75

0

0.106667

75

2

49

37.5

0.970149

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

6650ece9eff653fec0a780c57d465c6ed9f75645

63

py

Python

labs/code/packages/usemymath.py

Linlin15963/msds501

0bcfa7f59a4e9b2d71db2c5973eb04c1ae60e72f

[ "MIT" ]

86

2018-08-14T20:13:32.000Z

2022-03-21T22:30:15.000Z

labs/code/packages/usemymath.py

Linlin15963/msds501

0bcfa7f59a4e9b2d71db2c5973eb04c1ae60e72f

[ "MIT" ]

2

2017-07-21T02:02:25.000Z

2017-09-13T03:19:09.000Z

labs/code/packages/usemymath.py

Linlin15963/msds501

0bcfa7f59a4e9b2d71db2c5973eb04c1ae60e72f

[ "MIT" ]

99

2015-02-28T20:10:38.000Z

2018-07-30T20:24:43.000Z

from mymath import * print(pi) print(pow2(0)) print(pow2(10))

10.5

20

0.698413

11

63

4

0.727273

0.409091

0

0.090909

0.126984

63

5

21

12.6

0.709091

0

1

0

true

0

0.25

0

0.25

0.75

1

0

null

1

0

1

0

null

0

1

0

1

0

5

66535de2732e1d5ab114c90ef0998c9ad4943553

56

py

Python

medimodule/Brain/models/__init__.py

cuchoco/MI2RLNet

4ef84e641705df9b10e627c701eb0c9ed924a82a

[ "Apache-2.0" ]

9

2021-02-25T23:10:17.000Z

2022-02-14T11:48:11.000Z

medimodule/Brain/models/__init__.py

cuchoco/MI2RLNet

4ef84e641705df9b10e627c701eb0c9ed924a82a

[ "Apache-2.0" ]

null

medimodule/Brain/models/__init__.py

cuchoco/MI2RLNet

4ef84e641705df9b10e627c701eb0c9ed924a82a

[ "Apache-2.0" ]

7

2021-02-22T12:20:24.000Z

2022-03-07T04:56:53.000Z

from .mri_bet import MRIBET from .bbb_seg import BBBSeg

28

0.821429

10

56

4.4

0.8

0

0.142857

56

2

29

28

0.916667

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

b0764c98279ab2a712c4cdfcc31812582f80a408

119

py

Python

Chapter01/do_something.py

ibiscum/Python-Parallel-Programming-Cookbook-Second-Edition

8fd583019778b4d797d4f948d091b5564e23f732

[ "MIT" ]

null

Chapter01/do_something.py

ibiscum/Python-Parallel-Programming-Cookbook-Second-Edition

8fd583019778b4d797d4f948d091b5564e23f732

[ "MIT" ]

null

Chapter01/do_something.py

ibiscum/Python-Parallel-Programming-Cookbook-Second-Edition

8fd583019778b4d797d4f948d091b5564e23f732

[ "MIT" ]

null

import random def do_something(count, out_list): for i in range(count): out_list.append(random.random())

17

40

0.689076

18

119

4.388889

0.722222

0.202532

0.303797

0

0.201681

119

6

41

19.833333

0.831579

0

1

0.25

false

0

0.25

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

b0aadf625334de18a075e7eba79d0b2a34ce5efe

66

py

Python

sklearn_export/__init__.py

zwelz3/sklearn-export

6692d94f8a592e8f3c9f21d672d8aa814e4d1473

[ "MIT" ]

4

2019-03-02T14:18:36.000Z

2021-11-09T08:10:32.000Z

sklearn_export/__init__.py

zwelz3/sklearn-export

6692d94f8a592e8f3c9f21d672d8aa814e4d1473

[ "MIT" ]

3

2019-05-03T03:54:36.000Z

2022-02-14T03:57:24.000Z

sklearn_export/__init__.py

zwelz3/sklearn-export

6692d94f8a592e8f3c9f21d672d8aa814e4d1473

[ "MIT" ]

1

2022-02-21T00:46:29.000Z

# -*- coding: utf-8 -*- from sklearn_export.Export import Export

16.5

40

0.69697

9

66

5

0.777778

0

0.017857

0.151515

66

3

41

22

0.785714

0.318182

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

b0ad745de92261706fc5d3fa1e348b03bc4dbca7

268

py

Python

tests/bindings/test_starimport.py

garyo/godot-python

f3d70f4fcf88c865fc7b3b7ac9cf09f8c503a1aa

[ "MIT" ]

null

tests/bindings/test_starimport.py

garyo/godot-python

f3d70f4fcf88c865fc7b3b7ac9cf09f8c503a1aa

[ "MIT" ]

null

tests/bindings/test_starimport.py

garyo/godot-python

f3d70f4fcf88c865fc7b3b7ac9cf09f8c503a1aa

[ "MIT" ]

null

# This test is in it own file to protect other tests from the `import *` side effects from godot.bindings import * def test_starimport(): assert issubclass(Node, Object) assert isinstance(PhysicsServer, _PhysicsServer) assert isinstance(Engine, _Engine)

29.777778

85

0.757463

35

268

5.714286

0.771429

0.16

0

0.175373

268

8

86

33.5

0.904977

0.309701

0

0.6

1

0.2

true

0

0.4

0

0.6

0

null

0

1

0

null

0

1

0

1

0

1

0

1

0

5

b0045483f9d153ad4551abacdaaaa89fcb63f7cb

97

py

Python

tests/test_utils/constants.py

DenverCoder1/godel-number-to-code

1f4fc3d5eba97ca45411302a67db79c77e44e19d

[ "MIT" ]

null

tests/test_utils/constants.py

DenverCoder1/godel-number-to-code

1f4fc3d5eba97ca45411302a67db79c77e44e19d

[ "MIT" ]

null

tests/test_utils/constants.py

DenverCoder1/godel-number-to-code

1f4fc3d5eba97ca45411302a67db79c77e44e19d

[ "MIT" ]

1

2022-01-18T19:51:33.000Z

# program numbers BASIC = 140624 GOTO = 158250875866513204219300194287615 VARIABLES = 6198727823

19.4

40

0.835052

8

97

10.125

1

0

0.576471

0.123711

97

4

41

24.25

0.376471

0.154639

0

1

0

false

0

1

0

1

null

0

1

0

1

0

1

0

null

0

5

b05e498a8d968ae962d4f71fd69ee85e50d36b39

494

py

Python

osOperate.py

yvanwangl/pythonLesson

5b3892465a321b9f749ffda623f5871656bde608

[ "MIT" ]

null

osOperate.py

yvanwangl/pythonLesson

5b3892465a321b9f749ffda623f5871656bde608

[ "MIT" ]

null

osOperate.py

yvanwangl/pythonLesson

5b3892465a321b9f749ffda623f5871656bde608

[ "MIT" ]

null

import os import shutil # print(os.path.join('C:\\Users\\hanlu', 'testDir')) # os.mkdir('C:\\Users\\hanlu\\testDir') # os.rmdir('C:\\Users\\hanlu\\testDir') # os.path.split('C:\\Users\\hanlu\\testDir') # print([x for x in os.listdir('.') if os.path.isdir(x)]) # # shutil.copyfile('writeFiles/writeTemp.txt', 'writeFiles/copy.txt') # # print([x for x in os.listdir('.') if os.path.isfile(x) and os.path.splitext(x)[1] == '.py']) # os.rename('copy.txt', 'rename.txt') os.remove('rename.txt')

27.444444

94

0.643725

80

494

3.975

0.3875

0.09434

0.138365

0.226415

0.371069

0.18239

0

0.002232

0.093117

494

17

95

29.058824

0.707589

0.852227

0

0.16129

0

1

0

true

0

0.666667

0

0.666667

0

null

0

1

0

1

0

null

0

1

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1

0

1

0

5

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py

Python

trainer/__init__.py

Y-modify/DeepL2

e8ba0ad302ad8ed208b70695b6015f8c75a0496c

[ "MIT" ]

2

2019-02-17T03:54:52.000Z

2019-02-17T04:06:16.000Z

trainer/__init__.py

Y-modify/deepl2

e8ba0ad302ad8ed208b70695b6015f8c75a0496c

[ "MIT" ]

20

2019-01-06T09:15:11.000Z

2019-01-18T03:12:33.000Z

trainer/__init__.py

Y-modify/deepl2

e8ba0ad302ad8ed208b70695b6015f8c75a0496c

[ "MIT" ]

1

2019-01-06T09:12:52.000Z

from .train import train from .preview import preview from logging import NullHandler, getLogger getLogger(__name__).addHandler(NullHandler())

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py

Python

tahoe_scorm/exceptions.py

appsembler/tahoe-scorm

f5ad868d1ffc5c0de3b568319c808197e17b42e5

[ "MIT" ]

null

tahoe_scorm/exceptions.py

appsembler/tahoe-scorm

f5ad868d1ffc5c0de3b568319c808197e17b42e5

[ "MIT" ]

2

2020-11-04T15:15:42.000Z

2021-02-04T10:30:57.000Z

tahoe_scorm/exceptions.py

appsembler/tahoe-scorm

f5ad868d1ffc5c0de3b568319c808197e17b42e5

[ "MIT" ]

null

class ScormException(Exception): pass

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py

Python

src/__init__.py

hCraker/geocat-viz

7188ffdea3121d3368df2d1246e29d2d5825164c

[ "Apache-2.0" ]

null

src/__init__.py

hCraker/geocat-viz

7188ffdea3121d3368df2d1246e29d2d5825164c

[ "Apache-2.0" ]

null

src/__init__.py

hCraker/geocat-viz

7188ffdea3121d3368df2d1246e29d2d5825164c

[ "Apache-2.0" ]

null

from ._version import __version__ from . import util import cmaps

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py

Python

source/__init__.py

ml6jason/imgflow

deb31b72837d9e5cc5d7bed0ef980b330e4fd527

[ "BSD-2-Clause" ]

null

source/__init__.py

ml6jason/imgflow

deb31b72837d9e5cc5d7bed0ef980b330e4fd527

[ "BSD-2-Clause" ]

1

2020-11-24T22:42:28.000Z

source/__init__.py

ml6jason/imgflow

deb31b72837d9e5cc5d7bed0ef980b330e4fd527

[ "BSD-2-Clause" ]

null

from .core.loader import ClassificationDatasetLoader as LoadClassDataset from .core.loader import CVATDatasetLoader as LoadCVATDataset from .core.loader import DetectionResultLoader as LoadDetectionResults from .core.loader import LocalDirLoader as LocalDirLoader from .core.transform import ImgTransformSave as Save from .core.transform import ImgTransformResize as Resize from .core.transform import ImgTransformScale as Scale from .core.transform import ImgTransformExtractBboxes as ExtractBboxes

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py

Python

04/01/instance_method/astimezone.py

pylangstudy/201709

53d868786d7327a83bfa7f4149549c6f9855a6c6

[ "CC0-1.0" ]

null

04/01/instance_method/astimezone.py

pylangstudy/201709

53d868786d7327a83bfa7f4149549c6f9855a6c6

[ "CC0-1.0" ]

32

2017-09-01T00:52:17.000Z

2017-10-01T00:30:02.000Z

04/01/instance_method/astimezone.py

pylangstudy/201709

53d868786d7327a83bfa7f4149549c6f9855a6c6

[ "CC0-1.0" ]

null

import datetime now = datetime.datetime.now() print(now) print(now.astimezone())

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af864386ec13e2fcb5556eba73488a4420e97e8d

119

py

Python

{{cookiecutter.project_name}}/{{cookiecutter.project_name}}/apps/common/context_processors.py

vioquedu/django-redux-boilerplate

f63d7a99d825215ea4d5e2eb41bb6fc1be491718

[ "BSD-3-Clause" ]

5

2016-07-21T23:54:20.000Z

2017-07-26T20:36:25.000Z

{{cookiecutter.project_name}}/{{cookiecutter.project_name}}/apps/common/context_processors.py

vioquedu/django-redux-boilerplate

f63d7a99d825215ea4d5e2eb41bb6fc1be491718

[ "BSD-3-Clause" ]

5

2016-10-22T20:08:06.000Z

2017-01-12T13:01:42.000Z

{{cookiecutter.project_name}}/{{cookiecutter.project_name}}/apps/common/context_processors.py

vioquedu/django-redux-boilerplate

f63d7a99d825215ea4d5e2eb41bb6fc1be491718

[ "BSD-3-Clause" ]

null

from django.conf import settings def site_info(request): return { 'site_name': settings.SITE_NAME, }

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af8bad67d9b6377eb5eb30843f1e83d2aba77a3a

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py

Python

modules/networkx/algorithms/tests/test_mixing_degree.py

fstwn/Cockatoo

0c5f9c515053bfc31e62d20fddc4ae9bece09d88

[ "MIT" ]

9

2020-09-26T03:41:21.000Z

2021-11-29T06:52:35.000Z

modules/networkx/algorithms/tests/test_mixing_degree.py

fstwn/Cockatoo

0c5f9c515053bfc31e62d20fddc4ae9bece09d88

[ "MIT" ]

9

2020-08-10T19:38:03.000Z

2022-02-24T08:41:32.000Z

modules/networkx/algorithms/tests/test_mixing_degree.py

fstwn/Cockatoo

0c5f9c515053bfc31e62d20fddc4ae9bece09d88

[ "MIT" ]

7

2015-04-28T19:19:30.000Z

2022-02-06T11:46:29.000Z

#!/usr/bin/env python from nose.tools import * from nose import SkipTest import networkx import networkx.algorithms.mixing as mixing class TestDegreeMixing(object): def setUp(self): self.P4=networkx.path_graph(4) self.D=networkx.DiGraph() self.D.add_edges_from([(0, 2), (0, 3), (1, 3), (2, 3)]) self.M=networkx.MultiGraph() self.M.add_path(list(range(4))) self.M.add_edge(0,1) self.S=networkx.Graph() self.S.add_edges_from([(0,0),(1,1)]) def test_node_degree_xy_undirected(self): xy=sorted(mixing.node_degree_xy(self.P4)) xy_result=sorted([(1,2), (2,1), (2,2), (2,2), (1,2), (2,1)]) assert_equal(xy,xy_result) def test_node_degree_xy_directed(self): xy=sorted(mixing.node_degree_xy(self.D)) xy_result=sorted([(2,1), (2,3), (1,3), (1,3)]) assert_equal(xy,xy_result) def test_node_degree_xy_multigraph(self): xy=sorted(mixing.node_degree_xy(self.M)) xy_result=sorted([(2,3), (2,3), (3,2), (3,2), (2,3), (3,2), (1,2), (2,1)]) assert_equal(xy,xy_result) def test_node_degree_xy_selfloop(self): xy=sorted(mixing.node_degree_xy(self.S)) xy_result=sorted([(2,2), (2,2)]) assert_equal(xy,xy_result) def test_degree_mixing_dict_undirected(self): d=mixing.degree_mixing_dict(self.P4) d_result={1:{2:2}, 2:{1:2,2:2}, } assert_equal(d,d_result) def test_degree_mixing_dict_directed(self): d=mixing.degree_mixing_dict(self.D) print(d) d_result={1:{3:2}, 2:{1:1,3:1}, 3:{} } assert_equal(d,d_result) def test_degree_mixing_dict_multigraph(self): d=mixing.degree_mixing_dict(self.M) d_result={1:{2:1}, 2:{1:1,3:3}, 3:{2:3} } assert_equal(d,d_result) class TestDegreeMixingMatrix(object): @classmethod def setupClass(cls): global np global npt try: import numpy as np import numpy.testing as npt except ImportError: raise SkipTest('NumPy not available.') def setUp(self): self.P4=networkx.path_graph(4) self.D=networkx.DiGraph() self.D.add_edges_from([(0, 2), (0, 3), (1, 3), (2, 3)]) self.M=networkx.MultiGraph() self.M.add_path(list(range(4))) self.M.add_edge(0,1) self.S=networkx.Graph() self.S.add_edges_from([(0,0),(1,1)]) def test_degree_mixing_matrix_undirected(self): a_result=np.array([[0,0,0], [0,0,2], [0,2,2]] ) a=mixing.degree_mixing_matrix(self.P4,normalized=False) npt.assert_equal(a,a_result) a=mixing.degree_mixing_matrix(self.P4) npt.assert_equal(a,a_result/float(a_result.sum())) def test_degree_mixing_matrix_directed(self): a_result=np.array([[0,0,0,0], [0,0,0,2], [0,1,0,1], [0,0,0,0]] ) a=mixing.degree_mixing_matrix(self.D,normalized=False) npt.assert_equal(a,a_result) a=mixing.degree_mixing_matrix(self.D) npt.assert_equal(a,a_result/float(a_result.sum())) def test_degree_mixing_matrix_multigraph(self): a_result=np.array([[0,0,0,0], [0,0,1,0], [0,1,0,3], [0,0,3,0]] ) a=mixing.degree_mixing_matrix(self.M,normalized=False) npt.assert_equal(a,a_result) a=mixing.degree_mixing_matrix(self.M) npt.assert_equal(a,a_result/float(a_result.sum())) def test_degree_mixing_matrix_selfloop(self): a_result=np.array([[0,0,0], [0,0,0], [0,0,2]] ) a=mixing.degree_mixing_matrix(self.S,normalized=False) npt.assert_equal(a,a_result) a=mixing.degree_mixing_matrix(self.S) npt.assert_equal(a,a_result/float(a_result.sum())) def test_degree_assortativity_undirected(self): r=mixing.degree_assortativity(self.P4) npt.assert_almost_equal(r,-1.0/2,decimal=4) def test_degree_assortativity_directed(self): r=mixing.degree_assortativity(self.D) npt.assert_almost_equal(r,-0.57735,decimal=4) def test_degree_assortativity_multigraph(self): r=mixing.degree_assortativity(self.M) npt.assert_almost_equal(r,-1.0/7.0,decimal=4) class TestDegreeMixingMatrixPearsonr(object): @classmethod def setupClass(cls): global np global npt try: import numpy as np import numpy.testing as npt except ImportError: raise SkipTest('NumPy not available.') try: import scipy except ImportError: raise SkipTest('SciPy not available.') def setUp(self): self.P4=networkx.path_graph(4) self.D=networkx.DiGraph() self.D.add_edges_from([(0, 2), (0, 3), (1, 3), (2, 3)]) self.M=networkx.MultiGraph() self.M.add_path(list(range(4))) self.M.add_edge(0,1) self.S=networkx.Graph() self.S.add_edges_from([(0,0),(1,1)]) def test_degree_assortativity_undirected(self): r=mixing.degree_pearsonr(self.P4) npt.assert_almost_equal(r,-1.0/2,decimal=4) def test_degree_assortativity_directed(self): r=mixing.degree_pearsonr(self.D) npt.assert_almost_equal(r,-0.57735,decimal=4) def test_degree_assortativity_multigraph(self): r=mixing.degree_pearsonr(self.M) npt.assert_almost_equal(r,-1.0/7.0,decimal=4)

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py

Python

aerofiles/openair/__init__.py

flyingjoe/aerofiles

ac5775dbd47335e24aceb5df9d744192a46177f6

[ "MIT" ]

26

2015-04-17T08:24:13.000Z

2022-01-25T00:19:04.000Z

aerofiles/openair/__init__.py

GliderGeek/aerofiles

24b212547dec5a85c7d41c6924598f353d0fbb77

[ "MIT" ]

100

2015-04-17T04:46:50.000Z

2021-04-04T07:08:59.000Z

aerofiles/openair/__init__.py

GliderGeek/aerofiles

24b212547dec5a85c7d41c6924598f353d0fbb77

[ "MIT" ]

26

2015-04-17T04:09:19.000Z

2021-09-29T11:33:50.000Z

# flake8: noqa from .reader import Reader, LowLevelReader

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py

Python

main.py

jwrobel12/get-the-subway

aaa301883c32f1b12993b2e0a7767b941e2ea258

[ "MIT" ]

null

main.py

jwrobel12/get-the-subway

aaa301883c32f1b12993b2e0a7767b941e2ea258

[ "MIT" ]

null

main.py

jwrobel12/get-the-subway

aaa301883c32f1b12993b2e0a7767b941e2ea258

[ "MIT" ]

null

from functions import my_functions my_functions.hello("s")

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py

Python

src/airfly/_vendor/airflow/operators/google_api_to_s3_transfer.py

ryanchao2012/airfly

230ddd88885defc67485fa0c51f66c4a67ae98a9

[ "MIT" ]

7

2021-09-27T11:38:48.000Z

2022-02-01T06:06:24.000Z

src/airfly/_vendor/airflow/operators/google_api_to_s3_transfer.py

ryanchao2012/airfly

230ddd88885defc67485fa0c51f66c4a67ae98a9

[ "MIT" ]

null

src/airfly/_vendor/airflow/operators/google_api_to_s3_transfer.py

ryanchao2012/airfly

230ddd88885defc67485fa0c51f66c4a67ae98a9

[ "MIT" ]

null

# Auto generated by 'inv collect-airflow' from airfly._vendor.airflow.providers.amazon.aws.transfers.google_api_to_s3 import ( GoogleApiToS3Operator, ) class GoogleApiToS3Transfer(GoogleApiToS3Operator): pass

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py

Python

setup/utils/config_parsers/user.py

mnguyen-io/polkadot_api_server

b6a4aa6bdebce0b4a78e60f3681edd179e631577

[ "Apache-2.0" ]

32

2020-02-06T19:06:40.000Z

2022-03-08T23:02:56.000Z

setup/utils/config_parsers/user.py

mnguyen-io/polkadot_api_server

b6a4aa6bdebce0b4a78e60f3681edd179e631577

[ "Apache-2.0" ]

25

2020-03-11T20:45:12.000Z

2022-02-01T16:30:52.000Z

setup/utils/config_parsers/user.py

mnguyen-io/polkadot_api_server

b6a4aa6bdebce0b4a78e60f3681edd179e631577

[ "Apache-2.0" ]

22

2020-03-03T04:42:50.000Z

2021-08-29T21:50:36.000Z

class NodeConfig: def __init__(self, node_name: str, ws_url: str) -> None: self.node_name = node_name self.ws_url = ws_url

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py

Python

tests/__init__.py

msicilia/uprof_ont

97bdfae68edecfc4bc198a3da28ebea99e2fabfd

[ "MIT" ]

null

tests/__init__.py

msicilia/uprof_ont

97bdfae68edecfc4bc198a3da28ebea99e2fabfd

[ "MIT" ]

null

tests/__init__.py

msicilia/uprof_ont

97bdfae68edecfc4bc198a3da28ebea99e2fabfd

[ "MIT" ]

null

"""Unit test package for uprof_ont."""

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406

py

Python

typhon/core/type_system/constraints/base_constraint.py

strongrex2001/typhon

7a8ad7e0252768844009ab331fc8aa61350f23a9

[ "Apache-2.0" ]

4

2021-03-03T12:44:34.000Z

2021-07-03T10:15:43.000Z

typhon/core/type_system/constraints/base_constraint.py

eliphatfs/typhon

7a8ad7e0252768844009ab331fc8aa61350f23a9

[ "Apache-2.0" ]

null

typhon/core/type_system/constraints/base_constraint.py

eliphatfs/typhon

7a8ad7e0252768844009ab331fc8aa61350f23a9

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """ Created on Sat Mar 13 21:31:02 2021 @author: eliphat """ class BaseConstraint: def cause_vars(self): raise NotImplementedError() def effect_vars(self): raise NotImplementedError() def fix(self, ts): raise NotImplementedError() def is_resolved(self): # is_resolved will be called after fix raise NotImplementedError()

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py

Python

instapp/admin.py

imekenye/Instagram-clone

19c895a7bc4d5137f8df6eab7ade3920dfc3eb39

[ "Unlicense" ]

null

instapp/admin.py

imekenye/Instagram-clone

19c895a7bc4d5137f8df6eab7ade3920dfc3eb39

[ "Unlicense" ]

13

2020-02-12T00:19:23.000Z

2022-03-11T23:47:08.000Z

instapp/admin.py

imekenye/Instagram-clone

19c895a7bc4d5137f8df6eab7ade3920dfc3eb39

[ "Unlicense" ]

1

2019-06-07T10:01:06.000Z

from django.contrib import admin from .models import Image,UserProfile admin.site.register(Image) admin.site.register(UserProfile) # Register your models here.

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6

0.545455

0.136364

0.257576

0

0.110429

163

8

38

20.375

0.910345

0.159509

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

bbea6f18f807d1e95d88cbbf8bec51c445d775c2

18

py

Python

iotas/devices/philips/hue/__init__.py

jpwarren/holideck

4fd39f5cf5bd3a1749d5c57f1a73ea70fd9a8f49

[ "MIT" ]

2

2016-12-09T22:53:24.000Z

2016-12-21T11:15:04.000Z

iotas/devices/philips/hue/__init__.py

jpwarren/holideck

4fd39f5cf5bd3a1749d5c57f1a73ea70fd9a8f49

[ "MIT" ]

null

iotas/devices/philips/hue/__init__.py

jpwarren/holideck

4fd39f5cf5bd3a1749d5c57f1a73ea70fd9a8f49

[ "MIT" ]

null

print "Hello hue"

9

17

0.722222

3

18

4.333333

1

0

0.166667

18

1

18

0.866667

0

0.5

0

null

0

null

1

0

null

0

1

0

null

0

1

0

1

0

5